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All publications in 2010
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Modeling Interaction via the Principle of Maximum Causal Entropy
Brian D. Ziebart, J. A. Bagnell and Anind K. Dey
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


Conditional Topic Random Fields
Jun Zhu and Eric P. Xing
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


Cognitive Models of Test-Item Effects in Human Category Learning
Xiaojin Zhu, Bryan R. Gibson, Kwang-sung Jun, Timothy T. Rogers, Joseph Harrison and Chuck Kalish
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


OTL: A Framework of Online Transfer Learning
Peilin Zhao and Steven C. Hoi
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


Projection Penalties: Dimension Reduction without Loss
Yi Zhang and Jeff G. Schneider
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


Improved Local Coordinate Coding using Local Tangents
Kai Yu and Tong Zhang
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


Convergence of Least Squares Temporal Difference Methods Under General Conditions
Huizhen Yu
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


Online Learning for Group Lasso
Haiqin Yang, Zenglin Xu, Irwin King and Michael R. Lyu
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


Learning from Noisy Side Information by Generalized Maximum Entropy Model
Tianbao Yang, Rong Jin and Anil K. Jain
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


Sparse Gaussian Process Regression via L1 Penalization
Feng Yan and Yuan (. Qi
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


Simple and Efficient Multiple Kernel Learning by Group Lasso
Zenglin Xu, Rong Jin, Haiqin Yang, Irwin King and Michael R. Lyu
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


Detecting Large-Scale System Problems by Mining Console Logs
Wei Xu, Ling Huang, Armando Fox, David A. Patterson and Michael I. Jordan
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


Classes of Multiagent Q-learning Dynamics with epsilon-greedy Exploration
Michael Wunder, Michael L. Littman and Monica Babes
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


Online Streaming Feature Selection
Xindong Wu, Kui Yu, Hao Wang and Wei Ding
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


The IBP Compound Dirichlet Process and its Application to Focused Topic Modeling
Sinead Williamson, Chong Wang, Katherine A. Heller and David M. Blei
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


A New Analysis of Co-Training
Wei Wang and Zhi-hua Zhou
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


Sequential Projection Learning for Hashing with Compact Codes
Jun Wang, Sanjiv Kumar and Shih-fu Chang
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


Multi-Class Pegasos on a Budget
Zhuang Wang, Koby Crammer and Slobodan Vucetic
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


Generalizing Apprenticeship Learning across Hypothesis Classes
Thomas J. Walsh, Kaushik Subramanian, Michael L. Littman and Carlos Diuk
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


The Translation-invariant Wishart-Dirichlet Process for Clustering Distance Data
Julia E. Vogt, Sandhya Prabhakaran, Thomas J. Fuchs and Volker Roth
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


Non-Local Contrastive Objectives
David Vickrey, Cliff C. Lin and Daphne Koller
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


One-sided Support Vector Regression for Multiclass Cost-sensitive Classification
Han-hsing Tu and Hsuan-tien Lin
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


A Fast Augmented Lagrangian Algorithm for Learning Low-Rank Matrices
Ryota Tomioka, Taiji Suzuki, Masashi Sugiyama and Hisashi Kashima
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


An Analysis of the Convergence of Graph Laplacians
Daniel Ting, Ling Huang and Michael I. Jordan
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


Least-Squares Policy Iteration: Bias-Variance Trade-off in Control Problems
Christophe Thiery and Bruno Scherrer
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


A DC Programming Approach for Sparse Eigenvalue Problem
Mamadou Thiao, Pham D. Tao and Le An
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


Deep networks for robust visual recognition
Yichuan Tang and Chris Eliasmith
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


Learning Sparse SVM for Feature Selection on Very High Dimensional Datasets
Mingkui Tan, Li Wang and Ivor W. Tsang
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


Total Variation, Cheeger Cuts
Xavier Bresson and Arthur D. Szlam
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


Model-based reinforcement learning with nearly tight exploration complexity bounds
Istvan Szita and Csaba Szepesvári
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


Unsupervised Risk Stratification in Clinical Datasets: Identifying Patients at Risk of Rare Outcomes
Zeeshan Syed and Ilan Rubinfeld
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


Gaussian Process Optimization in the Bandit Setting: No Regret and Experimental Design
Niranjan Srinivas, Andreas Krause, Matthias Seeger and Sham M. Kakade
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


Internal Rewards Mitigate Agent Boundedness
Jonathan Sorg, Satinder P. Singh and Richard L. Lewis
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


COFFIN: A Computational Framework for Linear SVMs
Sören Sonnenburg and Vojtech Franc
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


Hilbert Space Embeddings of Hidden Markov Models
Le Song, Byron Boots, Sajid M. Siddiqi, Geoffrey J. Gordon and Alex J. Smola
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


Climbing the Tower of Babel: Unsupervised Multilingual Learning
Benjamin Snyder and Regina Barzilay
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


Learning optimally diverse rankings over large document collections
Aleksandrs Slivkins, Filip Radlinski and Sreenivas Gollapudi
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


Application of Machine Learning To Epileptic Seizure Detection
Ali H. Shoeb and John V. Guttag
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


Gaussian Covariance and Scalable Variational Inference
Matthias Seeger
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


Should one compute the Temporal Difference fix point or minimize the Bellman Residual? The unified oblique projection view
Bruno Scherrer
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


Active Risk Estimation
Christoph Sawade, Niels Landwehr, Steffen Bickel and Tobias Scheffer
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


Learning Deep Boltzmann Machines using Adaptive MCMC
Ruslan Salakhutdinov
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


Online Prediction with Privacy
Jun Sakuma and Hiromi Arai
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


Gaussian Process Change Point Models
Yunus Saatci, Ryan D. Turner and Carl E. Rasmussen
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


Clustering processes
Daniil Ryabko
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


SVM Classifier Estimation from Group Probabilities
Stefan Rüping
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


A fast natural Newton method
Nicolas L. Roux and Andrew W. Fitzgibbon
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


Spherical Topic Models
Joseph Reisinger, Austin Waters, Bryan Silverthorn and Raymond J. Mooney
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


Music Plus One and Machine Learning
Christopher Raphael
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


Variable Selection in Model-Based Clustering: To Do or To Facilitate
Leonard Poon, Nevin L. Zhang, Tao Chen and Yi Wang
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


Feature Selection Using Regularization in Approximate Linear Programs for Markov Decision Processes
Marek Petrik, Gavin Taylor, Ronald Parr and Shlomo Zilberstein
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


Boosting for Regression Transfer
David Pardoe and Peter Stone
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


The Margin Perceptron with Unlearning
Constantinos Panagiotakopoulos and Petroula Tsampouka
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


A Stick-Breaking Construction of the Beta Process
John W. Paisley, Aimee K. Zaas, Christopher W. Woods, Geoffrey S. Ginsburg and Lawrence Carin
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


Multiagent Inductive Learning: an Argumentation-based Approach
Santiago Ontañón and Enric Plaza
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


Multiple Non-Redundant Spectral Clustering Views
Donglin Niu, Jennifer G. Dy and Michael I. Jordan
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


Estimation of (near) low-rank matrices with noise and high-dimensional scaling
Sahand Negahban and Martin J. Wainwright
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


Implicit Regularization in Variational Bayesian Matrix Factorization
Shinichi Nakajima and Masashi Sugiyama
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


Rectified Linear Units Improve Restricted Boltzmann Machines
Vinod Nair and Geoffrey E. Hinton
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


Nonparametric Return Distribution Approximation for Reinforcement Learning
Tetsuro Morimura, Masashi Sugiyama, Hisashi Kashima, Hirotaka Hachiya and Toshiyuki Tanaka
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


Deep Supervised t-Distributed Embedding
Martin R. Min, Laurens Maaten, Zineng Yuan, Anthony J. Bonner and Zhaolei Zhang
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


Learning Efficiently with Approximate Inference via Dual Losses
Ofer Meshi, David Sontag, Amir Globerson and Tommi S. Jaakkola
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


Metric Learning to Rank
Brian Mcfee and Gert R. Lanckriet
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


Exploiting Data-Independence for Fast Belief-Propagation
Julian J. Mcauley and Tibério S. Caetano
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


From Transformation-Based Dimensionality Reduction to Feature Selection
Mahdokht Masaeli, Jennifer G. Dy and Glenn M. Fung
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


Learning the Linear Dynamical System with ASOS
James Martens
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


Deep learning via Hessian-free optimization
James Martens
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


Constructing States for Reinforcement Learning
M. Mahmud
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


Toward Off-Policy Learning Control with Function Approximation
Hamid R. Maei, Csaba Szepesvári, Shalabh Bhatnagar and Richard S. Sutton
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


Mixed Membership Matrix Factorization
Lester W. Mackey, David Weiss and Michael I. Jordan
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


Restricted Boltzmann Machines are Hard to Approximately Evaluate or Simulate
Philip M. Long and Rocco Servedio
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


Efficient Reinforcement Learning with Multiple Reward Functions for Randomized Controlled Trial Analysis
Daniel J. Lizotte, Michael H. Bowling and Susan A. Murphy
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


Robust Graph Mode Seeking by Graph Shift
Hairong Liu and Shuicheng Yan
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


Learning Temporal Causal Graphs for Relational Time-Series Analysis
Yan Liu, Alexandru Niculescu-mizil, Aurelie C. Lozano and Yong Lu
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


Robust Subspace Segmentation by Low-Rank Representation
Guangcan Liu, Zhouchen Lin and Yong Yu
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


Large Graph Construction for Scalable Semi-Supervised Learning
Wei Liu, Junfeng He and Shih-fu Chang
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


Power Iteration Clustering
Frank Lin and William W. Cohen
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


On the Interaction between Norm and Dimensionality: Multiple Regimes in Learning
Percy Liang and Nati Srebro
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


Learning Programs: A Hierarchical Bayesian Approach
Percy Liang, Michael I. Jordan and Dan Klein
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


Budgeted Distribution Learning of Belief Net Parameters
Liuyang Li, Barnabás Póczos, Csaba Szepesvári and Russell Greiner
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


Making Large-Scale Nystr{\"o}m Approximation Possible
Mu Li, James T. Kwok and Bao-liang Lu
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


Finite-Sample Analysis of LSTD
Alessandro Lazaric, Mohammad Ghavamzadeh and Rémi Munos
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


Analysis of a Classification-based Policy Iteration Algorithm
Alessandro Lazaric, Mohammad Ghavamzadeh and Rémi Munos
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


Bayesian Multi-Task Reinforcement Learning
Alessandro Lazaric and Mohammad Ghavamzadeh
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


Supervised Aggregation of Classifiers using Artificial Prediction Markets
Nathan Lay and Adrian Barbu
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


Probabilistic Backward and Forward Reasoning in Stochastic Relational Worlds
Tobias Lang and Marc Toussaint
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


Implicit Online Learning
Brian Kulis and Peter L. Bartlett
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


Inverse Optimal Control with Linearly-Solvable MDPs
Krishnamurthy Dvijotham and Emanuel Todorov
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


Submodular Dictionary Selection for Sparse Representation
Andreas Krause and Volkan Cevher
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


On Sparse Nonparametric Conditional Covariance Selection
Mladen Kolar, Ankur P. Parikh and Eric P. Xing
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


Learning Markov Logic Networks Using Structural Motifs
Stanley Kok and Pedro Domingos
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


Tree-Guided Group Lasso for Multi-Task Regression with Structured Sparsity
Seyoung Kim and Eric P. Xing
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


Gaussian Processes Multiple Instance Learning
Minyoung Kim and Fernando Torre
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


Local Minima Embedding
Minyoung Kim and Fernando Torre
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


A scalable trust-region algorithm with application to mixed-norm regression
Dongmin Kim, Suvrit Sra and Inderjit S. Dhillon
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


Efficient Selection of Multiple Bandit Arms: Theory and Practice
Shivaram Kalyanakrishnan and Peter Stone
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


Accelerated dual decomposition for MAP inference
Vladimir Jojic, Stephen Gould and Daphne Koller
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


3D Convolutional Neural Networks for Human Action Recognition
Shuiwang Ji, Wei Xu, Ming Yang and Kai Yu
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


Proximal Methods for Sparse Hierarchical Dictionary Learning
Rodolphe Jenatton, Julien Mairal, Francis R. Bach and Guillaume R. Obozinski
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


Telling cause from effect based on high-dimensional observations
Dominik Janzing, Patrik O. Hoyer and Bernhard Schölkopf
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


A Simple Algorithm for Nuclear Norm Regularized Problems
Martin Jaggi and Marek Sulovsk\'y
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


On learning with kernels for unordered pairs
Martial Hue and Jean-philippe Vert
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


Learning Hierarchical Riffle Independent Groupings from Rankings
Jonathan Huang and Carlos Guestrin
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


Multi-Task Learning of Gaussian Graphical Models
Jean Honorio and Dimitris Samaras
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


Bayesian Nonparametric Matrix Factorization for Recorded Music
David M. Blei, Perry R. Cook and Matthew Hoffman
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


Active Learning for Multi-Task Adaptive Filtering
Abhay Harpale and Yiming Yang
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


Large Scale Max-Margin Multi-Label Classification with Priors
Bharath Hariharan, Lihi Zelnik-manor, Manik Varma and S.v.n. Vishwanathan
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


Interactive Submodular Set Cover
Andrew Guillory and Jeff A. Bilmes
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


Boosted Backpropagation Learning for Training Deep Modular Networks
Alexander Grubb and J. A. Bagnell
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


Learning Fast Approximations of Sparse Coding
Karol Gregor and Yann Lecun
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


Web-Scale Bayesian Click-Through rate Prediction for Sponsored Search Advertising in Microsoft's Bing Search Engine
Thore Graepel, Joaquin Q. Candela, Thomas Borchert and Ralf Herbrich
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


Budgeted Nonparametric Learning from Data Streams
Andreas Krause and Ryan G. Gomes
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


Boosting Classifiers with Tightened L0-Relaxation Penalties
Noam Goldberg and Jonathan Eckstein
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


A Language-based Approach to Measuring Scholarly Impact
Sean Gerrish and David M. Blei
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


Multiscale Wavelets on Trees, Graphs and High Dimensional Data: Theory and Applications to Semi Supervised Learning
Matan Gavish, Boaz Nadler and Ronald R. Coifman
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


Feature Selection as a One-Player Game
Romaric Gaudel and Michele Sebag
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


Discriminative Latent Variable Models for Object Detection
Pedro F. Felzenszwalb, Ross B. Girshick, David A. Mcallester and Deva Ramanan
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


Nonparametric Information Theoretic Clustering Algorithm
Lev Faivishevsky and Jacob Goldberger
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


On the Consistency of Ranking Algorithms
John C. Duchi, Lester W. Mackey and Michael I. Jordan
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


High-Performance Semi-Supervised Learning using Discriminatively Constrained Generative Models
Gregory Druck and Andrew Mccallum
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


Temporal Difference Bayesian Model Averaging: A Bayesian Perspective on Adapting Lambda
Carlton Downey and Scott Sanner
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


Heterogeneous Continuous Dynamic Bayesian Networks with Flexible Structure and Inter-Time Segment Information Sharing
Frank Dondelinger, Dirk Husmeier and Sophie Lebre
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


Approximate Predictive Representations of Partially Observable Systems
Monica Dinculescu and Doina Precup
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


Asymptotic Analysis of Generative Semi-Supervised Learning
Joshua V. Dillon, Krishnakumar Balasubramanian and Guy Lebanon
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


A Conditional Random Field for Multiple-Instance Learning
Thomas Deselaers and Vittorio Ferrari
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


Bayes Optimal Multilabel Classification via Probabilistic Classifier Chains
Weiwei Cheng, Eyke Hüllermeier and Krzysztof J. Dembczynski
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


Bottom-Up Learning of Markov Network Structure
Jesse Davis and Pedro Domingos
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


Mining Clustering Dimensions
Sajib Dasgupta and Vincent Ng
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


FAB-MAP: Appearance-Based Place Recognition and Mapping using a Learned Visual Vocabulary Model
Mark J. Cummins and Paul M. Newman
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


Fast Neighborhood Subgraph Pairwise Distance Kernel
Fabrizio Costa and Kurt D. Grave
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


Generalization Bounds for Learning Kernels
Corinna Cortes, Mehryar Mohri and Afshin Rostamizadeh
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


Two-Stage Learning Kernel Algorithms
Corinna Cortes, Mehryar Mohri and Afshin Rostamizadeh
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


Comparing Clusterings in Space
Michael H. Coen, M. H. Ansari and Nathanael Fillmore
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


Graded Multilabel Classification: The Ordinal Case
Weiwei Cheng, Eyke Hüllermeier and Krzysztof J. Dembczynski
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


Label Ranking Methods based on the Plackett-Luce Model
Weiwei Cheng, Eyke Hüllermeier and Krzysztof J. Dembczynski
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


Dynamical Products of Experts for Modeling Financial Time Series
Yutian Chen and Max Welling
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


Structured Output Learning with Indirect Supervision
Ming-wei Chang, Vivek Srikumar, Dan Goldwasser and Dan Roth
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


Transfer Learning for Collective Link Prediction in Multiple Heterogenous Domains
Bin Cao, Nathan N. Liu and Qiang Yang
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


Finding Planted Partitions in Nearly Linear Time using Arrested Spectral Clustering
Nader H. Bshouty and Philip M. Long
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


Learning Tree Conditional Random Fields
Joseph K. Bradley and Carlos Guestrin
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


Multi-agent Learning Experiments on Repeated Matrix Games
Bruno Bouzy and Marc Métivier
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


A Theoretical Analysis of Feature Pooling in Visual Recognition
Y-lan Boureau, Jean Ponce and Yann Lecun
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


Label Ranking under Ambiguous Supervision for Learning Semantic Correspondences
Antoine Bordes, Nicolas Usunier and Jason Weston
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


Causal filter selection in microarray data
Gianluca Bontempi and Patrick E. Meyer
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


Distance dependent Chinese restaurant processes
David M. Blei and Peter Frazier
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


Active Learning for Networked Data
Mustafa Bilgic, Lilyana Mihalkova and Lise Getoor
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


Robust Formulations for Handling Uncertainty in Kernel Matrices
Sahely Bhadra, Sourangshu Bhattacharya, Chiranjib Bhattacharyya and Aharon Ben-tal
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


Forgetting Counts: Constant Memory Inference for a Dependent Hierarchical Pitman-Yor Process
Nicholas Bartlett, David Pfau and Frank Wood
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


Surrogating the surrogate: accelerating Gaussian-process-based global optimization with a mixture cross-entropy algorithm
Rémi Bardenet and Balázs Kégl
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


Particle Filtered MCMC-MLE with Connections to Contrastive Divergence
Arthur U. Asuncion, Qiang Liu, Alexander T. Ihler and Padhraic Smyth
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


The Role of Machine Learning in Business Optimization
Chid Apté
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


Block Variable Selection in Multivariate Regression and High-dimensional Causal Inference
Vikas Sindhwani and Aurelie C. Lozano
Advances in Neural Information Processing Systems 23, 2010


On the Theory of Learnining with Privileged Information
Dmitry Pechyony and Vladimir Vapnik
Advances in Neural Information Processing Systems 23, 2010


A unified model of short-range and long-range motion perception
Shuang Wu, Xuming He, Hongjing Lu and Alan L. Yuille
Advances in Neural Information Processing Systems 23, 2010


A Bayesian Approach to Concept Drift
Stephen Bach and Mark Maloof
Advances in Neural Information Processing Systems 23, 2010


Smoothness, Low Noise and Fast Rates
Nathan Srebro, Karthik Sridharan and Ambuj Tewari
Advances in Neural Information Processing Systems 23, 2010


Sidestepping Intractable Inference with Structured Ensemble Cascades
David Weiss, Benjamin Sapp and Ben Taskar
Advances in Neural Information Processing Systems 23, 2010


Online Markov Decision Processes under Bandit Feedback
Gergely Neu, Andras Antos, András György and Csaba Szepesvári
Advances in Neural Information Processing Systems 23, 2010


Sparse Instrumental Variables (SPIV) for Genome-Wide Studies
Paul Mckeigue, Jon Krohn, Amos J. Storkey and Felix V. Agakov
Advances in Neural Information Processing Systems 23, 2010


Towards Property-Based Classification of Clustering Paradigms
Margareta Ackerman, Shai Ben-david and David Loker
Advances in Neural Information Processing Systems 23, 2010


Random Conic Pursuit for Semidefinite Programming
Ariel Kleiner, Ali Rahimi and Michael I. Jordan
Advances in Neural Information Processing Systems 23, 2010


Humans Learn Using Manifolds, Reluctantly
Tim Rogers, Chuck Kalish, Joseph Harrison, Xiaojin Zhu and Bryan R. Gibson
Advances in Neural Information Processing Systems 23, 2010


Regularized estimation of image statistics by Score Matching
Diederik P. Kingma and Yann L. Cun
Advances in Neural Information Processing Systems 23, 2010


Structural epitome: a way to summarize one’s visual experience
Nebojsa Jojic, Alessandro Perina and Vittorio Murino
Advances in Neural Information Processing Systems 23, 2010


Trading off Mistakes and Don't-Know Predictions
Amin Sayedi, Morteza Zadimoghaddam and Avrim Blum
Advances in Neural Information Processing Systems 23, 2010


Computing Marginal Distributions over Continuous Markov Networks for Statistical Relational Learning
Matthias Broecheler and Lise Getoor
Advances in Neural Information Processing Systems 23, 2010


Online Learning for Latent Dirichlet Allocation
Matthew Hoffman, Francis R. Bach and David M. Blei
Advances in Neural Information Processing Systems 23, 2010


Convex Multiple-Instance Learning by Estimating Likelihood Ratio
Fuxin Li and Cristian Sminchisescu
Advances in Neural Information Processing Systems 23, 2010


Auto-Regressive HMM Inference with Incomplete Data for Short-Horizon Wind Forecasting
Chris Barber, Joseph Bockhorst and Paul Roebber
Advances in Neural Information Processing Systems 23, 2010


Predicting Execution Time of Computer Programs Using Sparse Polynomial Regression
Ling Huang, Jinzhu Jia, Bin Yu, Byung-gon Chun, Petros Maniatis and Mayur Naik
Advances in Neural Information Processing Systems 23, 2010


Probabilistic Inference and Differential Privacy
Oliver Williams and Frank Mcsherry
Advances in Neural Information Processing Systems 23, 2010


Batch Bayesian Optimization via Simulation Matching
Javad Azimi, Alan Fern and Xiaoli Z. Fern
Advances in Neural Information Processing Systems 23, 2010


Energy Disaggregation via Discriminative Sparse Coding
J. Z. Kolter, Siddharth Batra and Andrew Y. Ng
Advances in Neural Information Processing Systems 23, 2010


Probabilistic latent variable models for distinguishing between cause and effect
Oliver Stegle, Dominik Janzing, Kun Zhang, Joris M. Mooij and Bernhard Schölkopf
Advances in Neural Information Processing Systems 23, 2010


Online Learning: Random Averages, Combinatorial Parameters, and Learnability
Alexander Rakhlin, Karthik Sridharan and Ambuj Tewari
Advances in Neural Information Processing Systems 23, 2010


A Theory of Multiclass Boosting
Indraneel Mukherjee and Robert E. Schapire
Advances in Neural Information Processing Systems 23, 2010


Learning concept graphs from text with stick-breaking priors
America Chambers, Padhraic Smyth and Mark Steyvers
Advances in Neural Information Processing Systems 23, 2010


Infinite Relational Modeling of Functional Connectivity in Resting State fMRI
Morten Mørup, Kristoffer Madsen, Anne-marie Dogonowski, Hartwig Siebner and Lars K. Hansen
Advances in Neural Information Processing Systems 23, 2010


On the Convexity of Latent Social Network Inference
Seth Myers and Jure Leskovec
Advances in Neural Information Processing Systems 23, 2010


Linear Complementarity for Regularized Policy Evaluation and Improvement
Jeffrey Johns, Christopher Painter-wakefield and Ronald Parr
Advances in Neural Information Processing Systems 23, 2010


Lower Bounds on Rate of Convergence of Cutting Plane Methods
Xinhua Zhang, Ankan Saha and S.v.n. Vishwanathan
Advances in Neural Information Processing Systems 23, 2010


Switched Latent Force Models for Movement Segmentation
Mauricio Alvarez, Jan R. Peters, Neil D. Lawrence and Bernhard Schölkopf
Advances in Neural Information Processing Systems 23, 2010


Size Matters: Metric Visual Search Constraints from Monocular Metadata
Mario Fritz, Kate Saenko and Trevor Darrell
Advances in Neural Information Processing Systems 23, 2010


Learning Convolutional Feature Hierarchies for Visual Recognition
Koray Kavukcuoglu, Pierre Sermanet, Y-lan Boureau, Karol Gregor, Michael Mathieu and Yann L. Cun
Advances in Neural Information Processing Systems 23, 2010


Sphere Embedding: An Application to Part-of-Speech Induction
Yariv Maron, Elie Bienenstock and Michael James
Advances in Neural Information Processing Systems 23, 2010


Linear readout from a neural population with partial correlation data
Adrien Wohrer, Ranulfo Romo and Christian K. Machens
Advances in Neural Information Processing Systems 23, 2010


CUR from a Sparse Optimization Viewpoint
Jacob Bien, Ya Xu and Michael W. Mahoney
Advances in Neural Information Processing Systems 23, 2010


Nonparametric Bayesian Policy Priors for Reinforcement Learning
Finale Doshi-velez, David Wingate, Nicholas Roy and Joshua B. Tenenbaum
Advances in Neural Information Processing Systems 23, 2010


The LASSO risk: asymptotic results and real world examples
Mohsen Bayati, José Pereira and Andrea Montanari
Advances in Neural Information Processing Systems 23, 2010


Evidence-Specific Structures for Rich Tractable CRFs
Anton Chechetka and Carlos Guestrin
Advances in Neural Information Processing Systems 23, 2010


Probabilistic Deterministic Infinite Automata
David Pfau, Nicholas Bartlett and Frank Wood
Advances in Neural Information Processing Systems 23, 2010


Predictive State Temporal Difference Learning
Byron Boots and Geoffrey J. Gordon
Advances in Neural Information Processing Systems 23, 2010


Repeated Games against Budgeted Adversaries
Jacob D. Abernethy and Manfred K. Warmuth
Advances in Neural Information Processing Systems 23, 2010


Short-term memory in neuronal networks through dynamical compressed sensing
Surya Ganguli and Haim Sompolinsky
Advances in Neural Information Processing Systems 23, 2010


A Dirty Model for Multi-task Learning
Ali Jalali, Sujay Sanghavi, Chao Ruan and Pradeep K. Ravikumar
Advances in Neural Information Processing Systems 23, 2010


Generating more realistic images using gated MRF's
Marc'aurelio Ranzato, Volodymyr Mnih and Geoffrey E. Hinton
Advances in Neural Information Processing Systems 23, 2010


Parallelized Stochastic Gradient Descent
Martin Zinkevich, Markus Weimer, Lihong Li and Alex J. Smola
Advances in Neural Information Processing Systems 23, 2010


Efficient and Robust Feature Selection via Joint ℓ2,1-Norms Minimization
Feiping Nie, Heng Huang, Xiao Cai and Chris H. Ding
Advances in Neural Information Processing Systems 23, 2010


Multi-label Multiple Kernel Learning by Stochastic Approximation: Application to Visual Object Recognition
Serhat Bucak, Rong Jin and Anil K. Jain
Advances in Neural Information Processing Systems 23, 2010


b-Bit Minwise Hashing for Estimating Three-Way Similarities
Ping Li, Arnd Konig and Wenhao Gui
Advances in Neural Information Processing Systems 23, 2010


Bootstrapping Apprenticeship Learning
Abdeslam Boularias and Brahim Chaib-draa
Advances in Neural Information Processing Systems 23, 2010


SpikeAnts, a spiking neuron network modelling the emergence of organization in a complex system
Sylvain Chevallier, Hél\`ene Paugam-moisy and Michele Sebag
Advances in Neural Information Processing Systems 23, 2010


An Inverse Power Method for Nonlinear Eigenproblems with Applications in 1-Spectral Clustering and Sparse PCA
Matthias Hein and Thomas Bühler
Advances in Neural Information Processing Systems 23, 2010


Fast detection of multiple change-points shared by many signals using group LARS
Jean-philippe Vert and Kevin Bleakley
Advances in Neural Information Processing Systems 23, 2010


Co-regularization Based Semi-supervised Domain Adaptation
Abhishek Kumar, Avishek Saha and Hal Daume
Advances in Neural Information Processing Systems 23, 2010


Empirical Bernstein Inequalities for U-Statistics
Thomas Peel, Sandrine Anthoine and Liva Ralaivola
Advances in Neural Information Processing Systems 23, 2010


Learning Multiple Tasks using Manifold Regularization
Arvind Agarwal, Samuel Gerber and Hal Daume
Advances in Neural Information Processing Systems 23, 2010


Efficient Optimization for Discriminative Latent Class Models
Armand Joulin, Jean Ponce and Francis R. Bach
Advances in Neural Information Processing Systems 23, 2010


Near-Optimal Bayesian Active Learning with Noisy Observations
Daniel Golovin, Andreas Krause and Debajyoti Ray
Advances in Neural Information Processing Systems 23, 2010


Deciphering subsampled data: adaptive compressive sampling as a principle of brain communication
Guy Isely, Christopher Hillar and Fritz Sommer
Advances in Neural Information Processing Systems 23, 2010


Approximate inference in continuous time Gaussian-Jump processes
Manfred Opper, Andreas Ruttor and Guido Sanguinetti
Advances in Neural Information Processing Systems 23, 2010


An Alternative to Low-level-Sychrony-Based Methods for Speech Detection
Javier R. Movellan and Paul L. Ruvolo
Advances in Neural Information Processing Systems 23, 2010


Learning Efficient Markov Networks
Vibhav Gogate, William Webb and Pedro Domingos
Advances in Neural Information Processing Systems 23, 2010


Global Analytic Solution for Variational Bayesian Matrix Factorization
Shinichi Nakajima, Masashi Sugiyama and Ryota Tomioka
Advances in Neural Information Processing Systems 23, 2010


Exact learning curves for Gaussian process regression on large random graphs
Matthew Urry and Peter Sollich
Advances in Neural Information Processing Systems 23, 2010


Deep Coding Network
Yuanqing Lin, Zhang Tong, Shenghuo Zhu and Kai Yu
Advances in Neural Information Processing Systems 23, 2010


Sample Complexity of Testing the Manifold Hypothesis
Hariharan Narayanan and Sanjoy Mitter
Advances in Neural Information Processing Systems 23, 2010


Non-Stochastic Bandit Slate Problems
Satyen Kale, Lev Reyzin and Robert E. Schapire
Advances in Neural Information Processing Systems 23, 2010


Brain covariance selection: better individual functional connectivity models using population prior
Gael Varoquaux, Alexandre Gramfort, Jean-baptiste Poline and Bertrand Thirion
Advances in Neural Information Processing Systems 23, 2010


Fast global convergence rates of gradient methods for high-dimensional statistical recovery
Alekh Agarwal, Sahand Negahban and Martin J. Wainwright
Advances in Neural Information Processing Systems 23, 2010


Network Flow Algorithms for Structured Sparsity
Julien Mairal, Rodolphe Jenatton, Francis R. Bach and Guillaume R. Obozinski
Advances in Neural Information Processing Systems 23, 2010


Constructing Skill Trees for Reinforcement Learning Agents from Demonstration Trajectories
George Konidaris, Scott Kuindersma, Roderic Grupen and Andre S. Barreto
Advances in Neural Information Processing Systems 23, 2010


Error Propagation for Approximate Policy and Value Iteration
Amir-massoud Farahmand, Csaba Szepesvári and Rémi Munos
Advances in Neural Information Processing Systems 23, 2010


Online Learning in The Manifold of Low-Rank Matrices
Uri Shalit, Daphna Weinshall and Gal Chechik
Advances in Neural Information Processing Systems 23, 2010


Inference and communication in the game of Password
Yang Xu and Charles Kemp
Advances in Neural Information Processing Systems 23, 2010


An analysis on negative curvature induced by singularity in multi-layer neural-network learning
Eiji Mizutani and Stuart Dreyfus
Advances in Neural Information Processing Systems 23, 2010


New Adaptive Algorithms for Online Classification
Francesco Orabona and Koby Crammer
Advances in Neural Information Processing Systems 23, 2010


A Bayesian Framework for Figure-Ground Interpretation
Vicky Froyen, Jacob Feldman and Manish Singh
Advances in Neural Information Processing Systems 23, 2010


A rational decision making framework for inhibitory control
Pradeep Shenoy, Angela J. Yu and Rajesh P. Rao
Advances in Neural Information Processing Systems 23, 2010


Active Learning Applied to Patient-Adaptive Heartbeat Classification
Jenna Wiens and John V. Guttag
Advances in Neural Information Processing Systems 23, 2010


Evaluation of Rarity of Fingerprints in Forensics
Chang Su and Sargur Srihari
Advances in Neural Information Processing Systems 23, 2010


Latent Variable Models for Predicting File Dependencies in Large-Scale Software Development
Diane Hu, Laurens Maaten, Youngmin Cho, Sorin Lerner and Lawrence K. Saul
Advances in Neural Information Processing Systems 23, 2010


Minimum Average Cost Clustering
Kiyohito Nagano, Yoshinobu Kawahara and Satoru Iwata
Advances in Neural Information Processing Systems 23, 2010


Improvements to the Sequence Memoizer
Jan Gasthaus and Yee W. Teh
Advances in Neural Information Processing Systems 23, 2010


Universal Kernels on Non-Standard Input Spaces
Andreas Christmann and Ingo Steinwart
Advances in Neural Information Processing Systems 23, 2010


Sodium entry efficiency during action potentials: A novel single-parameter family of Hodgkin-Huxley models
Anand Singh, Renaud Jolivet, Pierre Magistretti and Bruno Weber
Advances in Neural Information Processing Systems 23, 2010


Reward Design via Online Gradient Ascent
Jonathan Sorg, Richard L. Lewis and Satinder P. Singh
Advances in Neural Information Processing Systems 23, 2010


Subgraph Detection Using Eigenvector L1 Norms
Benjamin Miller, Nadya Bliss and Patrick J. Wolfe
Advances in Neural Information Processing Systems 23, 2010


MAP Estimation for Graphical Models by Likelihood Maximization
Akshat Kumar and Shlomo Zilberstein
Advances in Neural Information Processing Systems 23, 2010


Hallucinations in Charles Bonnet Syndrome Induced by Homeostasis: a Deep Boltzmann Machine Model
Peggy Series, David P. Reichert and Amos J. Storkey
Advances in Neural Information Processing Systems 23, 2010


Identifying graph-structured activation patterns in networks
James Sharpnack and Aarti Singh
Advances in Neural Information Processing Systems 23, 2010


Getting lost in space: Large sample analysis of the resistance distance
Ulrike V. Luxburg, Agnes Radl and Matthias Hein
Advances in Neural Information Processing Systems 23, 2010


Probabilistic Belief Revision with Structural Constraints
Peter Jones, Venkatesh Saligrama and Sanjoy Mitter
Advances in Neural Information Processing Systems 23, 2010


Link Discovery using Graph Feature Tracking
Emile Richard, Nicolas Baskiotis, Theodoros Evgeniou and Nicolas Vayatis
Advances in Neural Information Processing Systems 23, 2010


Throttling Poisson Processes
Uwe Dick, Peter Haider, Thomas Vanck, Michael Brückner and Tobias Scheffer
Advances in Neural Information Processing Systems 23, 2010


Improving Human Judgments by Decontaminating Sequential Dependencies
Harold Pashler, Matthew Wilder, Robert Lindsey, Matt Jones, Michael C. Mozer and Michael P. Holmes
Advances in Neural Information Processing Systems 23, 2010


Joint Cascade Optimization Using A Product Of Boosted Classifiers
Leonidas Lefakis and Francois Fleuret
Advances in Neural Information Processing Systems 23, 2010


Spike timing-dependent plasticity as dynamic filter
Joscha Schmiedt, Christian Albers and Klaus Pawelzik
Advances in Neural Information Processing Systems 23, 2010


Shadow Dirichlet for Restricted Probability Modeling
Bela Frigyik, Maya Gupta and Yihua Chen
Advances in Neural Information Processing Systems 23, 2010


Relaxed Clipping: A Global Training Method for Robust Regression and Classification
Min Yang, Linli Xu, Martha White, Dale Schuurmans and Yao-liang Yu
Advances in Neural Information Processing Systems 23, 2010


Pose-Sensitive Embedding by Nonlinear NCA Regression
Rob Fergus, George Williams, Ian Spiro, Christoph Bregler and Graham W. Taylor
Advances in Neural Information Processing Systems 23, 2010


Basis Construction from Power Series Expansions of Value Functions
Sridhar Mahadevan and Bo Liu
Advances in Neural Information Processing Systems 23, 2010


Global seismic monitoring as probabilistic inference
Nimar Arora, Stuart Russell, Paul Kidwell and Erik B. Sudderth
Advances in Neural Information Processing Systems 23, 2010


A Computational Decision Theory for Interactive Assistants
Alan Fern and Prasad Tadepalli
Advances in Neural Information Processing Systems 23, 2010


Movement extraction by detecting dynamics switches and repetitions
Silvia Chiappa and Jan R. Peters
Advances in Neural Information Processing Systems 23, 2010


Structured Determinantal Point Processes
Alex Kulesza and Ben Taskar
Advances in Neural Information Processing Systems 23, 2010


Structured sparsity-inducing norms through submodular functions
Francis R. Bach
Advances in Neural Information Processing Systems 23, 2010


Random Walk Approach to Regret Minimization
Hariharan Narayanan and Alexander Rakhlin
Advances in Neural Information Processing Systems 23, 2010


Direct Loss Minimization for Structured Prediction
Tamir Hazan, Joseph Keshet and David A. Mcallester
Advances in Neural Information Processing Systems 23, 2010


Inferring Stimulus Selectivity from the Spatial Structure of Neural Network Dynamics
Kanaka Rajan, L Abbott and Haim Sompolinsky
Advances in Neural Information Processing Systems 23, 2010


Implicit encoding of prior probabilities in optimal neural populations
Deep Ganguli and Eero P. Simoncelli
Advances in Neural Information Processing Systems 23, 2010


Variational bounds for mixed-data factor analysis
Mohammad E. Khan, Guillaume Bouchard, Kevin P. Murphy and Benjamin M. Marlin
Advances in Neural Information Processing Systems 23, 2010


Bayesian Action-Graph Games
Albert X. Jiang and Kevin Leyton-brown
Advances in Neural Information Processing Systems 23, 2010


A biologically plausible network for the computation of orientation dominance
Kritika Muralidharan and Nuno Vasconcelos
Advances in Neural Information Processing Systems 23, 2010


Approximate Inference by Compilation to Arithmetic Circuits
Daniel Lowd and Pedro Domingos
Advances in Neural Information Processing Systems 23, 2010


Multitask Learning without Label Correspondences
Novi Quadrianto, James Petterson, Tibério S. Caetano, Alex J. Smola and S.v.n. Vishwanathan
Advances in Neural Information Processing Systems 23, 2010


Robust PCA via Outlier Pursuit
Huan Xu, Constantine Caramanis and Sujay Sanghavi
Advances in Neural Information Processing Systems 23, 2010


Functional form of motion priors in human motion perception
Hongjing Lu, Tungyou Lin, Alan Lee, Luminita Vese and Alan L. Yuille
Advances in Neural Information Processing Systems 23, 2010


Slice sampling covariance hyperparameters of latent Gaussian models
Iain Murray and Ryan P. Adams
Advances in Neural Information Processing Systems 23, 2010


Stability Approach to Regularization Selection (StARS) for High Dimensional Graphical Models
Han Liu, Kathryn Roeder and Larry Wasserman
Advances in Neural Information Processing Systems 23, 2010


Parametric Bandits: The Generalized Linear Case
Sarah Filippi, Olivier Cappe, Aurélien Garivier and Csaba Szepesvári
Advances in Neural Information Processing Systems 23, 2010


Learning to combine foveal glimpses with a third-order Boltzmann machine
Hugo Larochelle and Geoffrey E. Hinton
Advances in Neural Information Processing Systems 23, 2010


Scrambled Objects for Least-Squares Regression
Odalric Maillard and Rémi Munos
Advances in Neural Information Processing Systems 23, 2010


Unsupervised Kernel Dimension Reduction
Meihong Wang, Fei Sha and Michael I. Jordan
Advances in Neural Information Processing Systems 23, 2010


Kernel Descriptors for Visual Recognition
Liefeng Bo, Xiaofeng Ren and Dieter Fox
Advances in Neural Information Processing Systems 23, 2010


Inter-time segment information sharing for non-homogeneous dynamic Bayesian networks
Dirk Husmeier, Frank Dondelinger and Sophie Lebre
Advances in Neural Information Processing Systems 23, 2010


More data means less inference: A pseudo-max approach to structured learning
David Sontag, Ofer Meshi, Amir Globerson and Tommi S. Jaakkola
Advances in Neural Information Processing Systems 23, 2010


Penalized Principal Component Regression on Graphs for Analysis of Subnetworks
Ali Shojaie and George Michailidis
Advances in Neural Information Processing Systems 23, 2010


Empirical Risk Minimization with Approximations of Probabilistic Grammars
Noah A. Smith and Shay B. Cohen
Advances in Neural Information Processing Systems 23, 2010


Deterministic Single-Pass Algorithm for LDA
Issei Sato, Kenichi Kurihara and Hiroshi Nakagawa
Advances in Neural Information Processing Systems 23, 2010


On a Connection between Importance Sampling and the Likelihood Ratio Policy Gradient
Tang Jie and Pieter Abbeel
Advances in Neural Information Processing Systems 23, 2010


Efficient algorithms for learning kernels from multiple similarity matrices with general convex loss functions
Achintya Kundu, Vikram Tankasali, Chiranjib Bhattacharyya and Aharon Ben-tal
Advances in Neural Information Processing Systems 23, 2010


Fractionally Predictive Spiking Neurons
Jaldert Rombouts and Sander M. Bohte
Advances in Neural Information Processing Systems 23, 2010


A POMDP Extension with Belief-dependent Rewards
Mauricio Araya, Olivier Buffet, Vincent Thomas and Françcois Charpillet
Advances in Neural Information Processing Systems 23, 2010


Multi-View Active Learning in the Non-Realizable Case
Wei Wang and Zhi-hua Zhou
Advances in Neural Information Processing Systems 23, 2010


Copula Processes
Andrew Wilson and Zoubin Ghahramani
Advances in Neural Information Processing Systems 23, 2010


Spectral Regularization for Support Estimation
Ernesto D. Vito, Lorenzo Rosasco and Alessandro Toigo
Advances in Neural Information Processing Systems 23, 2010


LSTD with Random Projections
Mohammad Ghavamzadeh, Alessandro Lazaric, Odalric Maillard and Rémi Munos
Advances in Neural Information Processing Systems 23, 2010


Collaborative Filtering in a Non-Uniform World: Learning with the Weighted Trace Norm
Nathan Srebro and Ruslan Salakhutdinov
Advances in Neural Information Processing Systems 23, 2010


A Primal-Dual Algorithm for Group Sparse Regularization with Overlapping Groups
Sofia Mosci, Silvia Villa, Alessandro Verri and Lorenzo Rosasco
Advances in Neural Information Processing Systems 23, 2010


Learning from Logged Implicit Exploration Data
Alex Strehl, John Langford, Lihong Li and Sham M. Kakade
Advances in Neural Information Processing Systems 23, 2010


Self-Paced Learning for Latent Variable Models
M. P. Kumar, Benjamin Packer and Daphne Koller
Advances in Neural Information Processing Systems 23, 2010


Rescaling, thinning or complementing? On goodness-of-fit procedures for point process models and Generalized Linear Models
Felipe Gerhard and Wulfram Gerstner
Advances in Neural Information Processing Systems 23, 2010


Causal discovery in multiple models from different experiments
Tom Claassen and Tom Heskes
Advances in Neural Information Processing Systems 23, 2010


Phoneme Recognition with Large Hierarchical Reservoirs
Fabian Triefenbach, Azarakhsh Jalalvand, Benjamin Schrauwen and Jean-pierre Martens
Advances in Neural Information Processing Systems 23, 2010


Efficient Relational Learning with Hidden Variable Detection
Ni Lao, Jun Zhu, Liu Xinwang, Yandong Liu and William W. Cohen
Advances in Neural Information Processing Systems 23, 2010


Hashing Hyperplane Queries to Near Points with Applications to Large-Scale Active Learning
Prateek Jain, Sudheendra Vijayanarasimhan and Kristen Grauman
Advances in Neural Information Processing Systems 23, 2010


Avoiding False Positive in Multi-Instance Learning
Yanjun Han, Qing Tao and Jue Wang
Advances in Neural Information Processing Systems 23, 2010


The Maximal Causes of Natural Scenes are Edge Filters
Jose Puertas, Joerg Bornschein and Joerg Luecke
Advances in Neural Information Processing Systems 23, 2010


Static Analysis of Binary Executables Using Structural SVMs
Nikos Karampatziakis
Advances in Neural Information Processing Systems 23, 2010


A novel family of non-parametric cumulative based divergences for point processes
Sohan Seth, Park Il, Austin Brockmeier, Mulugeta Semework, John Choi, Joseph Francis and Jose Principe
Advances in Neural Information Processing Systems 23, 2010


Heavy-Tailed Process Priors for Selective Shrinkage
Fabian L. Wauthier and Michael I. Jordan
Advances in Neural Information Processing Systems 23, 2010


Feature Set Embedding for Incomplete Data
David Grangier and Iain Melvin
Advances in Neural Information Processing Systems 23, 2010


A Reduction from Apprenticeship Learning to Classification
Umar Syed and Robert E. Schapire
Advances in Neural Information Processing Systems 23, 2010


Monte-Carlo Planning in Large POMDPs
David Silver and Joel Veness
Advances in Neural Information Processing Systems 23, 2010


Inference with Multivariate Heavy-Tails in Linear Models
Danny Bickson and Carlos Guestrin
Advances in Neural Information Processing Systems 23, 2010


Learning Bounds for Importance Weighting
Corinna Cortes, Yishay Mansour and Mehryar Mohri
Advances in Neural Information Processing Systems 23, 2010


Learning Networks of Stochastic Differential Equations
José Pereira, Morteza Ibrahimi and Andrea Montanari
Advances in Neural Information Processing Systems 23, 2010


The Neural Costs of Optimal Control
Samuel Gershman and Robert Wilson
Advances in Neural Information Processing Systems 23, 2010


Active Learning by Querying Informative and Representative Examples
Sheng-jun Huang, Rong Jin and Zhi-hua Zhou
Advances in Neural Information Processing Systems 23, 2010


Space-Variant Single-Image Blind Deconvolution for Removing Camera Shake
Stefan Harmeling, Hirsch Michael and Bernhard Schölkopf
Advances in Neural Information Processing Systems 23, 2010


Semi-Supervised Learning with Adversarially Missing Label Information
Umar Syed and Ben Taskar
Advances in Neural Information Processing Systems 23, 2010


Guaranteed Rank Minimization via Singular Value Projection
Prateek Jain, Raghu Meka and Inderjit S. Dhillon
Advances in Neural Information Processing Systems 23, 2010


Practical Large-Scale Optimization for Max-norm Regularization
Jason Lee, Ben Recht, Nathan Srebro, Joel Tropp and Ruslan Salakhutdinov
Advances in Neural Information Processing Systems 23, 2010


Extensions of Generalized Binary Search to Group Identification and Exponential Costs
Gowtham Bellala, Suresh Bhavnani and Clayton Scott
Advances in Neural Information Processing Systems 23, 2010


An Approximate Inference Approach to Temporal Optimization in Optimal Control
Konrad Rawlik, Marc Toussaint and Sethu Vijayakumar
Advances in Neural Information Processing Systems 23, 2010


Reverse Multi-Label Learning
James Petterson and Tibério S. Caetano
Advances in Neural Information Processing Systems 23, 2010


A Family of Penalty Functions for Structured Sparsity
Jean Morales, Charles A. Micchelli and Massimiliano Pontil
Advances in Neural Information Processing Systems 23, 2010


Boosting Classifier Cascades
Nuno Vasconcelos and Mohammad J. Saberian
Advances in Neural Information Processing Systems 23, 2010


Optimal Web-Scale Tiering as a Flow Problem
Gilbert Leung, Novi Quadrianto, Kostas Tsioutsiouliklis and Alex J. Smola
Advances in Neural Information Processing Systems 23, 2010


Active Instance Sampling via Matrix Partition
Yuhong Guo
Advances in Neural Information Processing Systems 23, 2010


Active Estimation of F-Measures
Christoph Sawade, Niels Landwehr and Tobias Scheffer
Advances in Neural Information Processing Systems 23, 2010


Natural Policy Gradient Methods with Parameter-based Exploration for Control Tasks
Atsushi Miyamae, Yuichi Nagata, Isao Ono and Shigenobu Kobayashi
Advances in Neural Information Processing Systems 23, 2010


Inductive Regularized Learning of Kernel Functions
Prateek Jain, Brian Kulis and Inderjit S. Dhillon
Advances in Neural Information Processing Systems 23, 2010


Optimal learning rates for Kernel Conjugate Gradient regression
Gilles Blanchard and Nicole Krämer
Advances in Neural Information Processing Systems 23, 2010


Moreau-Yosida Regularization for Grouped Tree Structure Learning
Jun Liu and Jieping Ye
Advances in Neural Information Processing Systems 23, 2010


Estimating Spatial Layout of Rooms using Volumetric Reasoning about Objects and Surfaces
Abhinav Gupta, Martial Hebert, Takeo Kanade and David M. Blei
Advances in Neural Information Processing Systems 23, 2010


Evaluating neuronal codes for inference using Fisher information
Haefner Ralf and Matthias Bethge
Advances in Neural Information Processing Systems 23, 2010


Gaussian Process Preference Elicitation
Shengbo Guo, Scott Sanner and Edwin V. Bonilla
Advances in Neural Information Processing Systems 23, 2010


The Multidimensional Wisdom of Crowds
Peter Welinder, Steve Branson, Pietro Perona and Serge J. Belongie
Advances in Neural Information Processing Systems 23, 2010


Learning sparse dynamic linear systems using stable spline kernels and exponential hyperpriors
Alessandro Chiuso and Gianluigi Pillonetto
Advances in Neural Information Processing Systems 23, 2010


Multi-Stage Dantzig Selector
Ji Liu, Peter Wonka and Jieping Ye
Advances in Neural Information Processing Systems 23, 2010


Word Features for Latent Dirichlet Allocation
James Petterson, Wray Buntine, Shravan M. Narayanamurthy, Tibério S. Caetano and Alex J. Smola
Advances in Neural Information Processing Systems 23, 2010


Worst-Case Linear Discriminant Analysis
Yu Zhang and Dit-yan Yeung
Advances in Neural Information Processing Systems 23, 2010


Effects of Synaptic Weight Diffusion on Learning in Decision Making Networks
Kentaro Katahira, Kazuo Okanoya and Masato Okada
Advances in Neural Information Processing Systems 23, 2010


Tiled convolutional neural networks
Jiquan Ngiam, Zhenghao Chen, Daniel Chia, Pang W. Koh, Quoc V. Le and Andrew Y. Ng
Advances in Neural Information Processing Systems 23, 2010


Individualized ROI Optimization via Maximization of Group-wise Consistency of Structural and Functional Profiles
Kaiming Li, Lei Guo, Carlos Faraco, Dajiang Zhu, Fan Deng, Tuo Zhang, Xi Jiang, Degang Zhang, Hanbo Chen, Xintao Hu, Steve Miller and Tianming Liu
Advances in Neural Information Processing Systems 23, 2010


A Log-Domain Implementation of the Diffusion Network in Very Large Scale Integration
Yi-da Wu, Shi-jie Lin and Hsin Chen
Advances in Neural Information Processing Systems 23, 2010


Lifted Inference Seen from the Other Side : The Tractable Features
Abhay Jha, Vibhav Gogate, Alexandra Meliou and Dan Suciu
Advances in Neural Information Processing Systems 23, 2010


Synergies in learning words and their referents
Mark Johnson, Katherine Demuth, Bevan Jones and Michael J. Black
Advances in Neural Information Processing Systems 23, 2010


Policy gradients in linearly-solvable MDPs
Emanuel Todorov
Advances in Neural Information Processing Systems 23, 2010


Learning the context of a category
Dan Navarro
Advances in Neural Information Processing Systems 23, 2010


Decoding Ipsilateral Finger Movements from ECoG Signals in Humans
Yuzong Liu, Mohit Sharma, Charles Gaona, Jonathan Breshears, Jarod Roland, Zachary Freudenburg, Eric Leuthardt and Kilian Q. Weinberger
Advances in Neural Information Processing Systems 23, 2010


Categories and Functional Units: An Infinite Hierarchical Model for Brain Activations
Danial Lashkari, Ramesh Sridharan and Polina Golland
Advances in Neural Information Processing Systems 23, 2010


Large Margin Multi-Task Metric Learning
Shibin Parameswaran and Kilian Q. Weinberger
Advances in Neural Information Processing Systems 23, 2010


Mixture of time-warped trajectory models for movement decoding
Elaine Corbett, Eric Perreault and Konrad Koerding
Advances in Neural Information Processing Systems 23, 2010


Group Sparse Coding with a Laplacian Scale Mixture Prior
Pierre Garrigues and Bruno A. Olshausen
Advances in Neural Information Processing Systems 23, 2010


Adaptive Multi-Task Lasso: with Application to eQTL Detection
Seunghak Lee, Jun Zhu and Eric P. Xing
Advances in Neural Information Processing Systems 23, 2010


Rates of convergence for the cluster tree
Kamalika Chaudhuri and Sanjoy Dasgupta
Advances in Neural Information Processing Systems 23, 2010


Identifying Dendritic Processing
Aurel A. Lazar and Yevgeniy Slutskiy
Advances in Neural Information Processing Systems 23, 2010


A Novel Kernel for Learning a Neuron Model from Spike Train Data
Nicholas Fisher and Arunava Banerjee
Advances in Neural Information Processing Systems 23, 2010


Attractor Dynamics with Synaptic Depression
K. Wong, He Wang, Si Wu and Chi Fung
Advances in Neural Information Processing Systems 23, 2010


Nonparametric Density Estimation for Stochastic Optimization with an Observable State Variable
Lauren Hannah, Warren Powell and David M. Blei
Advances in Neural Information Processing Systems 23, 2010


Efficient Minimization of Decomposable Submodular Functions
Peter Stobbe and Andreas Krause
Advances in Neural Information Processing Systems 23, 2010


Predictive Subspace Learning for Multi-view Data: a Large Margin Approach
Ning Chen, Jun Zhu and Eric P. Xing
Advances in Neural Information Processing Systems 23, 2010


Learning Multiple Tasks with a Sparse Matrix-Normal Penalty
Yi Zhang and Jeff G. Schneider
Advances in Neural Information Processing Systems 23, 2010


Discriminative Clustering by Regularized Information Maximization
Andreas Krause, Pietro Perona and Ryan G. Gomes
Advances in Neural Information Processing Systems 23, 2010


Graph-Valued Regression
Han Liu, Xi Chen, Larry Wasserman and John D. Lafferty
Advances in Neural Information Processing Systems 23, 2010


Worst-case bounds on the quality of max-product fixed-points
Meritxell Vinyals, Jes\'us Cerquides, Alessandro Farinelli and Juan A. Rodríguez-aguilar
Advances in Neural Information Processing Systems 23, 2010


Optimal Bayesian Recommendation Sets and Myopically Optimal Choice Query Sets
Paolo Viappiani and Craig Boutilier
Advances in Neural Information Processing Systems 23, 2010


Interval Estimation for Reinforcement-Learning Algorithms in Continuous-State Domains
Martha White and Adam White
Advances in Neural Information Processing Systems 23, 2010


Using body-anchored priors for identifying actions in single images
Leonid Karlinsky, Michael Dinerstein and Shimon Ullman
Advances in Neural Information Processing Systems 23, 2010


Learning invariant features using the Transformed Indian Buffet Process
Joseph L. Austerweil and Thomas L. Griffiths
Advances in Neural Information Processing Systems 23, 2010


Factorized Latent Spaces with Structured Sparsity
Yangqing Jia, Mathieu Salzmann and Trevor Darrell
Advances in Neural Information Processing Systems 23, 2010


On Herding and the Perceptron Cycling Theorem
Andrew Gelfand, Yutian Chen, Laurens Maaten and Max Welling
Advances in Neural Information Processing Systems 23, 2010


PAC-Bayesian Model Selection for Reinforcement Learning
Mahdi M. Fard and Joelle Pineau
Advances in Neural Information Processing Systems 23, 2010


Supervised Clustering
Pranjal Awasthi and Reza B. Zadeh
Advances in Neural Information Processing Systems 23, 2010


Implicit Differentiation by Perturbation
Justin Domke
Advances in Neural Information Processing Systems 23, 2010


A VLSI Implementation of the Adaptive Exponential Integrate-and-Fire Neuron Model
Sebastian Millner, Andreas Grübl, Karlheinz Meier, Johannes Schemmel and Marc-olivier Schwartz
Advances in Neural Information Processing Systems 23, 2010


Distributed Dual Averaging In Networks
Alekh Agarwal, Martin J. Wainwright and John C. Duchi
Advances in Neural Information Processing Systems 23, 2010


Variable margin losses for classifier design
Hamed Masnadi-shirazi and Nuno Vasconcelos
Advances in Neural Information Processing Systems 23, 2010


Joint Analysis of Time-Evolving Binary Matrices and Associated Documents
Eric Wang, Dehong Liu, Jorge Silva, Lawrence Carin and David B. Dunson
Advances in Neural Information Processing Systems 23, 2010


MAP estimation in Binary MRFs via Bipartite Multi-cuts
Sashank J. Reddi, Sunita Sarawagi and Sundar Vishwanathan
Advances in Neural Information Processing Systems 23, 2010


Multiparty Differential Privacy via Aggregation of Locally Trained Classifiers
Manas Pathak, Shantanu Rane and Bhiksha Raj
Advances in Neural Information Processing Systems 23, 2010


Sparse Coding for Learning Interpretable Spatio-Temporal Primitives
Taehwan Kim, Gregory Shakhnarovich and Raquel Urtasun
Advances in Neural Information Processing Systems 23, 2010


Multiple Kernel Learning and the SMO Algorithm
Zhaonan Sun, Nawanol Ampornpunt, Manik Varma and S.v.n. Vishwanathan
Advances in Neural Information Processing Systems 23, 2010


Large Margin Learning of Upstream Scene Understanding Models
Jun Zhu, Li-jia Li, Li Fei-fei and Eric P. Xing
Advances in Neural Information Processing Systems 23, 2010


A Primal-Dual Message-Passing Algorithm for Approximated Large Scale Structured Prediction
Tamir Hazan and Raquel Urtasun
Advances in Neural Information Processing Systems 23, 2010


Why are some word orders more common than others? A uniform information density account
Luke Maurits, Dan Navarro and Amy Perfors
Advances in Neural Information Processing Systems 23, 2010


Learning Kernels with Radiuses of Minimum Enclosing Balls
Kun Gai, Guangyun Chen and Chang-shui Zhang
Advances in Neural Information Processing Systems 23, 2010


Agnostic Active Learning Without Constraints
Alina Beygelzimer, John Langford, Zhang Tong and Daniel J. Hsu
Advances in Neural Information Processing Systems 23, 2010


Sufficient Conditions for Generating Group Level Sparsity in a Robust Minimax Framework
Hongbo Zhou and Qiang Cheng
Advances in Neural Information Processing Systems 23, 2010


A New Probabilistic Model for Rank Aggregation
Tao Qin, Xiubo Geng and Tie-yan Liu
Advances in Neural Information Processing Systems 23, 2010


Generative Local Metric Learning for Nearest Neighbor Classification
Yung-kyun Noh, Byoung-tak Zhang and Daniel D. Lee
Advances in Neural Information Processing Systems 23, 2010


Improving the Asymptotic Performance of Markov Chain Monte-Carlo by Inserting Vortices
Yi Sun, Jürgen Schmidhuber and Faustino J. Gomez
Advances in Neural Information Processing Systems 23, 2010


Simultaneous Object Detection and Ranking with Weak Supervision
Matthew Blaschko, Andrea Vedaldi and Andrew Zisserman
Advances in Neural Information Processing Systems 23, 2010


Learning To Count Objects in Images
Victor Lempitsky and Andrew Zisserman
Advances in Neural Information Processing Systems 23, 2010


Gated Softmax Classification
Roland Memisevic, Christopher Zach, Marc Pollefeys and Geoffrey E. Hinton
Advances in Neural Information Processing Systems 23, 2010


Dynamic Infinite Relational Model for Time-varying Relational Data Analysis
Katsuhiko Ishiguro, Tomoharu Iwata, Naonori Ueda and Joshua B. Tenenbaum
Advances in Neural Information Processing Systems 23, 2010


Learning via Gaussian Herding
Koby Crammer and Daniel D. Lee
Advances in Neural Information Processing Systems 23, 2010


Robust Clustering as Ensembles of Affinity Relations
Hairong Liu, Longin J. Latecki and Shuicheng Yan
Advances in Neural Information Processing Systems 23, 2010


Cross Species Expression Analysis using a Dirichlet Process Mixture Model with Latent Matchings
Ziv Bar-joseph and Hai-son P. Le
Advances in Neural Information Processing Systems 23, 2010


Probabilistic Multi-Task Feature Selection
Yu Zhang, Dit-yan Yeung and Qian Xu
Advances in Neural Information Processing Systems 23, 2010


Feature Transitions with Saccadic Search: Size, Color, and Orientation Are Not Alike
Stella X. Yu
Advances in Neural Information Processing Systems 23, 2010


Over-complete representations on recurrent neural networks can support persistent percepts
Shaul Druckmann and Dmitri B. Chklovskii
Advances in Neural Information Processing Systems 23, 2010


Label Embedding Trees for Large Multi-Class Tasks
Samy Bengio, Jason Weston and David Grangier
Advances in Neural Information Processing Systems 23, 2010


Multivariate Dyadic Regression Trees for Sparse Learning Problems
Han Liu and Xi Chen
Advances in Neural Information Processing Systems 23, 2010


Layered image motion with explicit occlusions, temporal consistency, and depth ordering
Deqing Sun, Erik B. Sudderth and Michael J. Black
Advances in Neural Information Processing Systems 23, 2010


Decomposing Isotonic Regression for Efficiently Solving Large Problems
Ronny Luss, Saharon Rosset and Moni Shahar
Advances in Neural Information Processing Systems 23, 2010


Distributionally Robust Markov Decision Processes
Huan Xu and Shie Mannor
Advances in Neural Information Processing Systems 23, 2010


Variational Inference over Combinatorial Spaces
Alexandre Bouchard-côté and Michael I. Jordan
Advances in Neural Information Processing Systems 23, 2010


Estimation of Renyi Entropy and Mutual Information Based on Generalized Nearest-Neighbor Graphs
Barnabás Póczos, Csaba Szepesvári and David Tax
Advances in Neural Information Processing Systems 23, 2010


(RF)^2 -- Random Forest Random Field
Nadia Payet and Sinisa Todorovic
Advances in Neural Information Processing Systems 23, 2010


Tight Sample Complexity of Large-Margin Learning
Sivan Sabato, Nathan Srebro and Naftali Tishby
Advances in Neural Information Processing Systems 23, 2010


Exact inference and learning for cumulative distribution functions on loopy graphs
Nebojsa Jojic, Chris Meek and Jim C. Huang
Advances in Neural Information Processing Systems 23, 2010


Online Classification with Specificity Constraints
Andrey Bernstein, Shie Mannor and Nahum Shimkin
Advances in Neural Information Processing Systems 23, 2010


Implicitly Constrained Gaussian Process Regression for Monocular Non-Rigid Pose Estimation
Mathieu Salzmann and Raquel Urtasun
Advances in Neural Information Processing Systems 23, 2010


Identifying Patients at Risk of Major Adverse Cardiovascular Events Using Symbolic Mismatch
Zeeshan Syed and John V. Guttag
Advances in Neural Information Processing Systems 23, 2010


Double Q-learning
Hado V. Hasselt
Advances in Neural Information Processing Systems 23, 2010


Layer-wise analysis of deep networks with Gaussian kernels
Grégoire Montavon, Klaus-robert Müller and Mikio L. Braun
Advances in Neural Information Processing Systems 23, 2010


Switching state space model for simultaneously estimating state transitions and nonstationary firing rates
Ken Takiyama and Masato Okada
Advances in Neural Information Processing Systems 23, 2010


Spatial and anatomical regularization of SVM for brain image analysis
Remi Cuingnet, Marie Chupin, Habib Benali and Olivier Colliot
Advances in Neural Information Processing Systems 23, 2010


Fast Large-scale Mixture Modeling with Component-specific Data Partitions
Bo Thiesson and Chong Wang
Advances in Neural Information Processing Systems 23, 2010


t-logistic regression
Nan Ding and S.v.n. Vishwanathan
Advances in Neural Information Processing Systems 23, 2010


Phone Recognition with the Mean-Covariance Restricted Boltzmann Machine
George Dahl, Marc'aurelio Ranzato, Abdel-rahman Mohamed and Geoffrey E. Hinton
Advances in Neural Information Processing Systems 23, 2010


Object Bank: A High-Level Image Representation for Scene Classification & Semantic Feature Sparsification
Li-jia Li, Hao Su, Li Fei-fei and Eric P. Xing
Advances in Neural Information Processing Systems 23, 2010


Transduction with Matrix Completion: Three Birds with One Stone
Andrew Goldberg, Ben Recht, Junming Xu, Robert Nowak and Xiaojin Zhu
Advances in Neural Information Processing Systems 23, 2010


Copula Bayesian Networks
Gal Elidan
Advances in Neural Information Processing Systems 23, 2010


Epitome driven 3-D Diffusion Tensor image segmentation: on extracting specific structures
Kamiya Motwani, Nagesh Adluru, Chris Hinrichs, Andrew Alexander and Vikas Singh
Advances in Neural Information Processing Systems 23, 2010


Feature Construction for Inverse Reinforcement Learning
Sergey Levine, Zoran Popovic and Vladlen Koltun
Advances in Neural Information Processing Systems 23, 2010


Tree-Structured Stick Breaking for Hierarchical Data
Zoubin Ghahramani, Michael I. Jordan and Ryan P. Adams
Advances in Neural Information Processing Systems 23, 2010


Learning to localise sounds with spiking neural networks
Dan Goodman and Romain Brette
Advances in Neural Information Processing Systems 23, 2010


Random Projection Trees Revisited
Aman Dhesi and Purushottam Kar
Advances in Neural Information Processing Systems 23, 2010


Two-Layer Generalization Analysis for Ranking Using Rademacher Average
Wei Chen, Tie-yan Liu and Zhi-ming Ma
Advances in Neural Information Processing Systems 23, 2010


Segmentation as Maximum-Weight Independent Set
William Brendel and Sinisa Todorovic
Advances in Neural Information Processing Systems 23, 2010


Large-Scale Matrix Factorization with Missing Data under Additional Constraints
Kaushik Mitra, Sameer Sheorey and Rama Chellappa
Advances in Neural Information Processing Systems 23, 2010


Towards Holistic Scene Understanding: Feedback Enabled Cascaded Classification Models
Congcong Li, Adarsh Kowdle, Ashutosh Saxena and Tsuhan Chen
Advances in Neural Information Processing Systems 23, 2010


Beyond Actions: Discriminative Models for Contextual Group Activities
Tian Lan, Yang Wang, Weilong Yang and Greg Mori
Advances in Neural Information Processing Systems 23, 2010


Random Projections for $k$-means Clustering
Christos Boutsidis, Anastasios Zouzias and Petros Drineas
Advances in Neural Information Processing Systems 23, 2010


Sparse Inverse Covariance Selection via Alternating Linearization Methods
Katya Scheinberg, Shiqian Ma and Donald Goldfarb
Advances in Neural Information Processing Systems 23, 2010


Learning from Candidate Labeling Sets
Jie Luo and Francesco Orabona
Advances in Neural Information Processing Systems 23, 2010


A Discriminative Latent Model of Image Region and Object Tag Correspondence
Yang Wang and Greg Mori
Advances in Neural Information Processing Systems 23, 2010


Exploiting weakly-labeled Web images to improve object classification: a domain adaptation approach
Alessandro Bergamo and Lorenzo Torresani
Advances in Neural Information Processing Systems 23, 2010


Accounting for network effects in neuronal responses using L1 regularized point process models
Ryan Kelly, Matthew Smith, Robert Kass and Tai S. Lee
Advances in Neural Information Processing Systems 23, 2010


Occlusion Detection and Motion Estimation with Convex Optimization
Alper Ayvaci, Michalis Raptis and Stefano Soatto
Advances in Neural Information Processing Systems 23, 2010


Divisive Normalization: Justification and Effectiveness as Efficient Coding Transform
Siwei Lyu
Advances in Neural Information Processing Systems 23, 2010


Functional Geometry Alignment and Localization of Brain Areas
Georg Langs, Yanmei Tie, Laura Rigolo, Alexandra Golby and Polina Golland
Advances in Neural Information Processing Systems 23, 2010


Gaussian sampling by local perturbations
George Papandreou and Alan L. Yuille
Advances in Neural Information Processing Systems 23, 2010


Construction of Dependent Dirichlet Processes based on Poisson Processes
Dahua Lin, Eric Grimson and John W. Fisher
Advances in Neural Information Processing Systems 23, 2010


Permutation Complexity Bound on Out-Sample Error
Malik Magdon-ismail
Advances in Neural Information Processing Systems 23, 2010


Extended Bayesian Information Criteria for Gaussian Graphical Models
Rina Foygel and Mathias Drton
Advances in Neural Information Processing Systems 23, 2010


Generalized roof duality and bisubmodular functions
Vladimir Kolmogorov
Advances in Neural Information Processing Systems 23, 2010


Universal Consistency of Multi-Class Support Vector Classification
Tobias Glasmachers
Advances in Neural Information Processing Systems 23, 2010


Exclusive Lasso for Multi-task Feature Selection
Yang Zhou, Rong Jin and Steven Hoi
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS-10), 2010


Multi-Task Learning using Generalized t Process
Yu Zhang and Dit-yan Yeung
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS-10), 2010


Risk Bounds for Levy Processes in the PAC-Learning Framework
Chao Zhang and Dacheng Tao
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS-10), 2010


Bayesian Online Learning for Multi-label and Multi-variate Performance Measures
Xinhua Zhang, Thore Graepel and Ralf Herbrich
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS-10), 2010


Bayesian Generalized Kernel Models
Zhihua Zhang, Guang Dai, Donghui Wang and Michael I. Jordan
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS-10), 2010


Matrix-Variate Dirichlet Process Mixture Models
Zhihua Zhang, Guang Dai and Michael I. Jordan
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS-10), 2010


A highly efficient blocked Gibbs sampler reconstruction of multidimensional NMR spectra
Ji W. Yoon, Simon P. Wilson and K. H. Mok
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS-10), 2010


Modeling annotator expertise: Learning when everybody knows a bit of something
Yan Yan, Rómer Rosales, Glenn Fung, Mark W. Schmidt, Gerardo H. Valadez, Luca Bogoni, Linda Moy and Jennifer G. Dy
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS-10), 2010


Dependent Indian Buffet Processes
Sinead Williamson, Peter Orbanz and Zoubin Ghahramani
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS-10), 2010


Structured Prediction Cascades
David Weiss and Ben Taskar
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS-10), 2010


Online Passive-Aggressive Algorithms on a Budget
Zhuang Wang and Slobodan Vucetic
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS-10), 2010


A Potential-based Framework for Online Multi-class Learning with Partial Feedback
Shijun Wang, Rong Jin and Hamed Valizadegan
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS-10), 2010


An Alternative Prior Process for Nonparametric Bayesian Clustering
Hanna M. Wallach, Shane Jensen, Lee Dicker and Katherine A. Heller
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS-10), 2010


Guarantees for Approximate Incremental SVMs
Nicolas Usunier, Antoine Bordes and Léon Bottou
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS-10), 2010


Sequential Monte Carlo Samplers for Dirichlet Process Mixtures
Yener Ülker, Bilge Günsel and Ali T. Cemgil
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS-10), 2010


State-Space Inference and Learning with Gaussian Processes
Ryan D. Turner, Marc P. Deisenroth and Carl E. Rasmussen
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS-10), 2010


Learning Causal Structure from Overlapping Variable Sets
Sofia Triantafilou, Ioannis Tsamardinos and Ioannis G. Tollis
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS-10), 2010


A Markov-Chain Monte Carlo Approach to Simultaneous Localization and Mapping
Péter Torma, András György and Csaba Szepesvári
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS-10), 2010


Bayesian Gaussian Process Latent Variable Model
Michalis K. Titsias and Neil D. Lawrence
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS-10), 2010


Unsupervised Aggregation for Classification Problems with Large Numbers of Categories
Ivan Titov, Alexandre Klementiev, Kevin Small and Dan Roth
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS-10), 2010


Learning Policy Improvements with Path Integrals
Evangelos Theodorou, Jonas Buchli and Stefan Schaal
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS-10), 2010


Hartigan's Method: k-means Clustering without Voronoi
Matus Telgarsky and Andrea Vattani
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS-10), 2010


HOP-MAP: Efficient Message Passing with High Order Potentials
Daniel Tarlow, Inmar E. Givoni and Richard S. Zemel
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS-10), 2010


Sufficient Dimension Reduction via Squared-loss Mutual Information Estimation
Taiji Suzuki and Masashi Sugiyama
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS-10), 2010


Inference and Learning in Networks of Queues
Charles A. Sutton and Michael I. Jordan
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS-10), 2010


On the Convergence Properties of Contrastive Divergence
Ilya Sutskever and Tijmen Tieleman
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS-10), 2010


Conditional Density Estimation via Least-Squares Density Ratio Estimation
Masashi Sugiyama, Ichiro Takeuchi, Taiji Suzuki, Takafumi Kanamori, Hirotaka Hachiya and Daisuke Okanohara
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS-10), 2010


On the relation between universality, characteristic kernels and RKHS embedding of measures
Bharath K. Sriperumbudur, Kenji Fukumizu and Gert Lanckriet
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS-10), 2010


Nonparametric Tree Graphical Models
Le Song, Arthur Gretton and Carlos Guestrin
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS-10), 2010


Inference of Sparse Networks with Unobserved Variables. Application to Gene Regulatory Networks
Nikolai Slavov
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS-10), 2010


Detecting Weak but Hierarchically-Structured Patterns in Networks
Aarti Singh, Robert D. Nowak and Robert Calderbank
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS-10), 2010


Reduced-Rank Hidden Markov Models
Sajid M. Siddiqi, Byron Boots and Geoffrey J. Gordon
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS-10), 2010


Empirical Bernstein Boosting
Pannagadatta K. Shivaswamy and Tony Jebara
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS-10), 2010


Dense Message Passing for Sparse Principal Component Analysis
Kevin Sharp and Magnus Rattray
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS-10), 2010


Polynomial-Time Exact Inference in NP-Hard Binary MRFs via Reweighted Perfect Matching
Nic Schraudolph
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS-10), 2010


Convex Structure Learning in Log-Linear Models: Beyond Pairwise Potentials
Mark W. Schmidt and Kevin P. Murphy
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS-10), 2010


Factorized Orthogonal Latent Spaces
Mathieu Salzmann, Carl H. Ek, Raquel Urtasun and Trevor Darrell
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS-10), 2010


Efficient Learning of Deep Boltzmann Machines
Ruslan Salakhutdinov and Hugo Larochelle
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS-10), 2010


Reducing Label Complexity by Learning From Bags
Sivan Sabato, Nathan Srebro and Naftali Tishby
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS-10), 2010


Active Sequential Learning with Tactile Feedback
Hannes P. Saal, Jo-anne Ting and Sethu Vijayakumar
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS-10), 2010


Approximate parameter inference in a stochastic reaction-diffusion model
Andreas Ruttor and Manfred Opper
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS-10), 2010


Efficient Reductions for Imitation Learning
Stéphane Ross and Drew Bagnell
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS-10), 2010


A Regularization Approach to Nonlinear Variable Selection
Lorenzo Rosasco, Matteo Santoro, Sofia Mosci, Alessandro Verri and Silvia Villa
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS-10), 2010


Gaussian processes with monotonicity information
Jaakko Riihimäki and Aki Vehtari
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS-10), 2010


Convexity of Proper Composite Binary Losses
Mark D. Reid and Robert C. Williamson
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS-10), 2010


Nonparametric prior for adaptive sparsity
Vikas C. Raykar and Linda H. Zhao
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS-10), 2010


Factored 3-Way Restricted Boltzmann Machines For Modeling Natural Images
Marc'aurelio Ranzato, Alex Krizhevsky and Geoffrey E. Hinton
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS-10), 2010


Infinite Predictor Subspace Models for Multitask Learning
Piyush Rai and Hal Daume
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS-10), 2010


REGO: Rank-based Estimation of Renyi Information using Euclidean Graph Optimization
Barnabás Póczos, Sergey Kirshner and Csaba Szepesvári
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS-10), 2010


Identifying Cause and Effect on Discrete Data using Additive Noise Models
Jonas Peters, Dominik Janzing and Bernhard Schölkopf
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS-10), 2010


Bayesian structure discovery in Bayesian networks with less space
Pekka Parviainen and Mikko Koivisto
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS-10), 2010


A generalization of the Multiple-try Metropolis algorithm for Bayesian estimation and model selection
Silvia Pandolfi, Francesco Bartolucci and Nial Friel
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS-10), 2010


Approximation of hidden Markov models by mixtures of experts with application to particle filtering
Jimmy Olsson and Jonas Ströjby
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS-10), 2010


Fluid Dynamics Models for Low Rank Discriminant Analysis
Yung-kyun Noh, Byoung-tak Zhang and Daniel D. Lee
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS-10), 2010


Incremental Sparsification for Real-time Online Model Learning
Duy Nguyen-tuong and Jan R. Peters
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS-10), 2010


Near-Optimal Evasion of Convex-Inducing Classifiers
Blaine Nelson, Ling Huang, Anthony D. Joseph, Shing-hon Lau, Steven J. Lee, Satish Rao, Anthony Tran, J. D. Tygar and Benjamin I. Rubinstein
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS-10), 2010


Elliptical slice sampling
Iain Murray, Ryan P. Adams and David Mackay
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS-10), 2010


Discriminative Topic Segmentation of Text and Speech
Mehryar Mohri, Pedro Moreno and Eugene Weinstein
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS-10), 2010


Exploiting Within-Clique Factorizations in Junction-Tree Algorithms
Julian J. Mcauley and Tibério S. Caetano
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS-10), 2010


Parallelizable Sampling of Markov Random Fields
James Martens and Ilya Sutskever
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS-10), 2010


Inductive Principles for Restricted Boltzmann Machine Learning
Benjamin M. Marlin, Kevin Swersky, Bo Chen and Nando D. Freitas
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS-10), 2010


Supervised Dimension Reduction Using Bayesian Mixture Modeling
Kai Mao, Feng Liang and Sayan Mukherjee
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS-10), 2010


Exploiting Feature Covariance in High-Dimensional Online Learning
Justin Ma, Alex Kulesza, Mark Dredze, Koby Crammer, Lawrence K. Saul and Fernando Pereira
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS-10), 2010


Contextual Multi-Armed Bandits
Tyler Lu, Dávid Pál and Martin Pal
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS-10), 2010


Descent Methods for Tuning Parameter Refinement
Alexander Lorbert and Peter J. Ramadge
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS-10), 2010


Exploiting Covariate Similarity in Sparse Regression via the Pairwise Elastic Net
Alexander Lorbert, David Eis, Victoria Kostina, David M. Blei and Peter J. Ramadge
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS-10), 2010


The Group Dantzig Selector
Han Liu, Jian Zhang, Xiaoye Jiang and Jun Liu
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS-10), 2010


Simple Exponential Family PCA
Jun Li and Dacheng Tao
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS-10), 2010


The Feature Selection Path in Kernel Methods
Fuxin Li and Cristian Sminchisescu
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS-10), 2010


Relating Function Class Complexity and Cluster Structure in the Function Domain with Applications to Transduction
Guy Lever
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS-10), 2010


Solving the Uncapacitated Facility Location Problem Using Message Passing Algorithms
Nevena Lazic, Brendan J. Frey and Parham Aarabi
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS-10), 2010


Semi-Supervised Learning with Max-Margin Graph Cuts
Branislav Kveton, Michal Valko, Ali Rahimi and Ling Huang
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS-10), 2010


Ultra-high Dimensional Multiple Output Learning With Simultaneous Orthogonal Matching Pursuit: Screening Approach
Mladen Kolar and Eric P. Xing
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS-10), 2010


Online Anomaly Detection under Adversarial Impact
Marius Kloft and Pavel Laskov
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS-10), 2010


Fast Active-set-type Algorithms for L1-regularized Linear Regression
Jingu Kim and Haesun Park
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS-10), 2010


Collaborative Filtering on a Budget
Alexandros Karatzoglou, Markus Weimer and Alex J. Smola
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS-10), 2010


Learning Exponential Families in High-Dimensions: Strong Convexity and Sparsity
Sham Kakade, Ohad Shamir, Karthik Sindharan and Ambuj Tewari
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS-10), 2010


Nonlinear functional regression: a functional RKHS approach
Hachem Kadri, Emmanuel Duflos, Philippe Preux, Stéphane Canu and Manuel Davy
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS-10), 2010


Structured Sparse Principal Component Analysis
Rodolphe Jenatton, Guillaume Obozinski and Francis R. Bach
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS-10), 2010


Learning Bayesian Network Structure using LP Relaxations
Tommi Jaakkola, David Sontag, Amir Globerson and Marina Meila
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS-10), 2010


Learning Nonlinear Dynamic Models from Non-sequenced Data
Tzu-kuo Huang, Le Song and Jeff G. Schneider
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS-10), 2010


Maximum-likelihood learning of cumulative distribution functions on graphs
Jim C. Huang and Nebojsa Jojic
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS-10), 2010


Collaborative Filtering via Rating Concentration
Bert C. Huang and Tony Jebara
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS-10), 2010


Coherent Inference on Optimal Play in Game Trees
Philipp Hennig, David H. Stern and Thore Graepel
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS-10), 2010


Negative Results for Active Learning with Convex Losses
Steve Hanneke and Liu Yang
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS-10), 2010


Dirichlet Process Mixtures of Generalized Linear Models
Lauren Hannah, David M. Blei and Warren B. Powell
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS-10), 2010


Boosted Optimization for Network Classification
Timothy Hancock and Hiroshi Mamitsuka
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS-10), 2010


Noise-contrastive estimation: A new estimation principle for unnormalized statistical models
Michael Gutmann and Aapo Hyvärinen
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS-10), 2010


Real-time Multiattribute Bayesian Preference Elicitation with Pairwise Comparison Queries
Shengbo Guo and Scott Sanner
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS-10), 2010


Sufficient covariates and linear propensity analysis
Hui Guo and A. P. Dawid
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS-10), 2010


Regret Bounds for Gaussian Process Bandit Problems
Steffen Grünewälder, Jean-yves Audibert, Manfred Opper and John Shawe-taylor
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS-10), 2010


Locally Linear Denoising on Image Manifolds
Dian Gong, Fei Sha and Gérard G. Medioni
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS-10), 2010


On Combining Graph-based Variance Reduction schemes
Vibhav Gogate and Rina Dechter
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS-10), 2010


Understanding the difficulty of training deep feedforward neural networks
Xavier Glorot and Yoshua Bengio
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS-10), 2010


Variational methods for Reinforcement Learning
Thomas Furmston and David Barber
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS-10), 2010


Posterior distributions are computable from predictive distributions
Cameron E. Freer and Daniel M. Roy
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS-10), 2010


A Weighted Multi-Sequence Markov Model For Brain Lesion Segmentation
Florence Forbes, Senan Doyle, Daniel Garc\'ıa-lorenzo, Christian Barillot and Michel Dojat
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS-10), 2010


Model-Free Monte Carlo-like Policy Evaluation
Raphael Fonteneau, Susan A. Murphy, Louis Wehenkel and Damien Ernst
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS-10), 2010


Semi-Supervised Learning via Generalized Maximum Entropy
Ayse Erkan and Yasemin Altun
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS-10), 2010


Why Does Unsupervised Pre-training Help Deep Learning?
Dumitru Erhan, Aaron C. Courville, Yoshua Bengio and Pascal Vincent
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS-10), 2010


Graphical Gaussian modelling of multivariate time series with latent variables
Michael Eichler
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS-10), 2010


Combining Experiments to Discover Linear Cyclic Models with Latent Variables
Frederick Eberhardt, Patrik O. Hoyer and Richard Scheines
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS-10), 2010


Neural conditional random fields
Trinh Do and Thierry Arti\`eres
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS-10), 2010


Nonparametric Bayesian Matrix Factorization by Power-EP
Nan Ding, Yuan (. Qi, Rongjing Xiang, Ian Molloy and Ninghui Li
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS-10), 2010


Bayesian variable order Markov models
Christos Dimitrakakis
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS-10), 2010


Feature Selection using Multiple Streams
Paramveer S. Dhillon, Dean P. Foster and Lyle H. Ungar
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS-10), 2010


Tempered Markov Chain Monte Carlo for training of Restricted Boltzmann Machines
Guillaume Desjardins, Aaron C. Courville, Yoshua Bengio, Pascal Vincent and Olivier Delalleau
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS-10), 2010


Multiclass-Multilabel Classification with More Classes than Examples
Ofer Dekel and Ohad Shamir
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS-10), 2010


Improving posterior marginal approximations in latent Gaussian models
Botond Cseke and Tom Heskes
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS-10), 2010


On the Impact of Kernel Approximation on Learning Accuracy
Corinna Cortes, Mehryar Mohri and Ameet Talwalkar
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS-10), 2010


Mass Fatality Incident Identification based on nuclear DNA evidence
Fabio Corradi
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS-10), 2010


Parametric Herding
Yutian Chen and Max Welling
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS-10), 2010


Focused Belief Propagation for Query-Specific Inference
Anton Chechetka and Carlos Guestrin
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS-10), 2010


Why are DBNs sparse?
Shaunak Chatterjee and Stuart Russell
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS-10), 2010


Using Descendants as Instrumental Variables for the Identification of Direct Causal Effects in Linear SEMs
Hei Chan and Manabu Kuroki
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS-10), 2010


Towards Understanding Situated Natural Language
Antoine Bordes, Nicolas Usunier, Ronan Collobert and Jason Weston
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS-10), 2010


Kernel Partial Least Squares is Universally Consistent
Gilles Blanchard and Nicole Krämer
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS-10), 2010


Impossibility Theorems for Domain Adaptation
Shai Ben-david, Tyler Lu, Teresa Luu and Dávid Pál
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS-10), 2010


Half Transductive Ranking
Bing Bai, Jason Weston, David Grangier, Ronan Collobert, Corinna Cortes and Mehryar Mohri
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS-10), 2010


Deterministic Bayesian inference for the p* model
Haakon Austad and Nial Friel
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS-10), 2010


Learning with Blocks: Composite Likelihood and Contrastive Divergence
Arthur U. Asuncion, Qiang Liu, Alexander T. Ihler and Padhraic Smyth
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS-10), 2010


Efficient Multioutput Gaussian Processes through Variational Inducing Kernels
Mauricio A. Álvarez, David Luengo, Michalis K. Titsias and Neil D. Lawrence
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS-10), 2010


Multitask Learning for Brain-Computer Interfaces
Morteza Alamgir, Moritz Grosse-wentrup and Yasemin Altun
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS-10), 2010


Optimal Allocation Strategies for the Dark Pool Problem
Alekh Agarwal, Peter L. Bartlett and Max Dama
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS-10), 2010


Learning the Structure of Deep Sparse Graphical Models
Ryan P. Adams, Hanna M. Wallach and Zoubin Ghahramani
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS-10), 2010