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All publications at Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07)
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Generalized Do-Calculus with Testable Causal Assumptions
Jiji Zhang
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


Importance Sampling for General Hybrid Bayesian Networks
Changhe Yuan and Marek J. Druzdzel
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


Nonnegative Garrote Component Selection in Functional ANOVA models
Ming Yuan
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


SVM versus Least Squares SVM
Jieping Ye and Tao Xiong
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


How Powerful Can Any Regression Learning Procedure Be?
Yuhong Yang
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


Transductive Classification via Local Learning Regularization
Mingrui Wu and Bernhard Schölkopf
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


Performance Guarantees for Information Theoretic Active Inference
Jason L. Williams, John Iii and Alan S. Willsky
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


Metric Learning for Kernel Regression
Kilian Q. Weinberger and Gerald Tesauro
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


The Kernel Path in Kernelized LASSO
Gang Wang, Dit-yan Yeung and Frederick H. Lochovsky
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


Semi-Supervised Mean Fields
Fei Wang, Shijun Wang, Changshui Zhang and Ole Winther
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


Fast Mean Shift with Accurate and Stable Convergence
Ping Wang, Dongryeol Lee, Alexander G. Gray and James M. Rehg
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


Efficient large margin semisupervised learning
Junhui Wang
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


Nonlinear Dimensionality Reduction as Information Retrieval
Jarkko Venna and Samuel Kaski
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


Hierarchical Beta Processes and the Indian Buffet Process
Romain Thibaux and Michael I. Jordan
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


Stick-breaking Construction for the Indian Buffet Process
Yee W. Teh, Dilan Görür and Zoubin Ghahramani
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


Learning Multilevel Distributed Representations for High-Dimensional Sequences
Ilya Sutskever and Geoffrey E. Hinton
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


Emerge and spread models and word burstiness
Peter Sunehag
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


Predictive Discretization during Model Selection
Harald Steck and Tommi Jaakkola
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


Local and global sparse Gaussian process approximations
Edward Snelson and Zoubin Ghahramani
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


Generalized Darting Monte Carlo
Cristian Sminchisescu and Max Welling
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


Dynamic Factorization Tests: Applications to Multi-modal Data Association
Michael Siracusa and John Iii
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


Analogical Reasoning with Relational Bayesian Sets
Ricardo Silva, Katherine A. Heller and Zoubin Ghahramani
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


Fast State Discovery for HMM Model Selection and Learning
Sajid M. Siddiqi, Geoffrey J. Gordon and Andrew W. Moore
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


Ellipsoidal Machines
Pannagadatta K. Shivaswamy and Tony Jebara
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


Fast Kernel ICA using an Approximate Newton Method
Hao Shen, Stefanie Jegelka and Arthur Gretton
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


A Framework for Probability Density Estimation
John Shawe-taylor and Alexander N. Dolia
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


Minimum Volume Embedding
Blake Shaw and Tony Jebara
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


A Unified Algorithmic Approach for Efficient Online Label Ranking
Shai Shalev-shwartz and Yoram Singer
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


Bayesian Inference and Optimal Design in the Sparse Linear Model
Matthias Seeger, Florian Steinke and Koji Tsuda
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


A Stochastic Quasi-Newton Method for Online Convex Optimization
Nicol N. Schraudolph, Jin Yu and Simon Günter
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


Memory-Effcient Orthogonal Least Squares Kernel Density Estimation using Enhanced Empirical Cumulative Distribution Functions
Martin Schafföner, Edin Andelic, Marcel Katz, Sven E. Krüger and Andreas Wendemuth
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


A Latent Space Approach to Dynamic Embedding of Co-occurrence Data
Purnamrita Sarkar, Sajid M. Siddiqi and Geoffrey J. Gordon
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


Learning a Nonlinear Embedding by Preserving Class Neighbourhood Structure
Ruslan Salakhutdinov and Geoffrey E. Hinton
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


Continuous Neural Networks
Nicolas L. Roux and Yoshua Bengio
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


The Rademacher Complexity of Co-Regularized Kernel Classes
David S. Rosenberg and Peter L. Bartlett
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


A fast algorithm for learning large scale preference relations
Vikas C. Raykar, Ramani Duraiswami and Balaji Krishnapuram
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


(Approximate) Subgradient Methods for Structured Prediction
Nathan D. Ratliff, J. A. Bagnell and Martin Zinkevich
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


A Unified Energy-Based Framework for Unsupervised Learning
Marc'aurelio Ranzato, Y-lan Boureau, Sumit Chopra and Yann Lecun
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


Approximate Counting of Graphical Models Via MCMC
Jose M. Peña
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


Margin based Transductive Graph Cuts using Linear Programming
Kristiaan Pelckmans, John Shawe-taylor, Johan Suykens and Bart D. Moor
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


Maximum Entropy Correlated Equilibria
Luis E. Ortiz, Robert E. Schapire and Sham M. Kakade
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


Inductive Transfer for Bayesian Network Structure Learning
Alexandru Niculescu-mizil and Rich Caruana
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


Loop Corrected Belief Propagation
Joris M. Mooij, Bastian Wemmenhove, Bert Kappen and Tommaso Rizzo
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


A Fast Bundle-based Anytime Algorithm for Poker and other Convex Games
H. B. Mcmahan and Geoffrey J. Gordon
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


AClass: A simple, online, parallelizable algorithm for probabilistic classification
Vikash K. Mansinghka, Daniel M. Roy, Ryan Rifkin and Joshua B. Tenenbaum
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


Recall Systems: Effcient Learning and Use of Category Indices
Omid Madani, Wiley Greiner, David Kempe and Mohammad R. Salavatipour
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


Semi-supervised Clustering with Pairwise Constraints: A Discriminative Approach
Zhengdong Lu
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


Sparse Nonparametric Density Estimation in High Dimensions Using the Rodeo
Han Liu, John D. Lafferty and Larry A. Wasserman
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


Fisher Consistency of Multicategory Support Vector Machines
Yufeng Liu
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


A Bayesian Divergence Prior for Classiffier Adaptation
Xiao Li and Jeff Bilmes
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


Efficient active learning with generalized linear models
Jeremy Lewi, Robert J. Butera and Liam Paninski
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


Treelets | A Tool for Dimensionality Reduction and Multi-Scale Analysis of Unstructured Data
Ann B. Lee and Boaz Nadler
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


Learning Nearest-Neighbor Quantizers from Labeled Data by Information Loss Minimization
Svetlana Lazebnik and Maxim Raginsky
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


Learning for Larger Datasets with the Gaussian Process Latent Variable Model
Neil D. Lawrence
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


Fast Low-Rank Semidefinite Programming for Embedding and Clustering
Brian Kulis, Arun C. Surendran and John C. Platt
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


Incorporating Prior Knowledge on Features into Learning
Eyal Krupka and Naftali Tishby
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


MDL Histogram Density Estimation
Petri Kontkanen and Petri Myllymäki
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


Multi-object tracking with representations of the symmetric group
Risi Kondor, Andrew Howard and Tony Jebara
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


Learning Markov Structure by Maximum Entropy Relaxation
Jason K. Johnson, Venkat Chandrasekaran and Alan S. Willsky
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


Loopy Belief Propagation for Bipartite Maximum Weight b-Matching
Bert C. Huang and Tony Jebara
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


A Nonparametric Bayesian Approach to Modeling Overlapping Clusters
Katherine A. Heller and Zoubin Ghahramani
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


Information Retrieval by Inferring Implicit Queries from Eye Movements
David R. Hardoon, John Shawe-taylor, Antti Ajanki, Kai Puolamäki and Samuel Kaski
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


Space-Efficient Sampling
Sudipto Guha and Andrew Mcgregor
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


Hidden Topic Markov Models
Amit Gruber, Yair Weiss and Michal Rosen-zvi
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


Dissimilarity in Graph-Based Semi-Supervised Classification
Andrew B. Goldberg, Xiaojin Zhu and Stephen J. Wright
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


SampleSearch: A Scheme that Searches for Consistent Samples
Vibhav Gogate and Rina Dechter
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


Visualizing pairwise similarity via semidefinite programming
Amir Globerson and Sam T. Roweis
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


Approximate inference using conditional entropy decompositions
Amir Globerson and Tommi Jaakkola
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


Deterministic Annealing for Multiple-Instance Learning
Peter V. Gehler and Olivier Chapelle
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


Online Learning of Search Heuristics
Michael Fink
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


Exact Bayesian structure learning from uncertain interventions
Daniel Eaton and Kevin P. Murphy
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


Learning A* underestimates: Using inference to guide inference
Gregory Druck, Mukund Narasimhan and Paul A. Viola
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


Large-Margin Classification in Banach Spaces
Ricky Der and Daniel Lee
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


Fast search for Dirichlet process mixture models
Hal Daume
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


Solving Markov Random Fields with Spectral Relaxation
Timothée Cour and Jianbo Shi
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


Visualizing Similarity Data with a Mixture of Maps
James Cook, Ilya Sutskever, Andriy Mnih and Geoffrey E. Hinton
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


The Laplacian Eigenmaps Latent Variable Model
Miguel Á. Carreira-perpiñán and Zhengdong Lu
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


A Hybrid Pareto Model for Conditional Density Estimation of Asymmetric Fat-Tail Data
Julie Carreau and Yoshua Bengio
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


Kernel Multi-task Learning using Task-specific Features
Edwin V. Bonilla, Felix V. Agakov and Christopher Williams
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


Mixture of Watson Distributions: A Generative Model for Hyperspherical Embeddings
Avleen S. Bijral, Markus Breitenbach and Gregory Z. Grudic
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


A Boosting Algorithm for Label Covering in Multilabel Problems
Yonatan Amit, Ofer Dekel and Yoram Singer
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


Seeking The Truly Correlated Topic Posterior - on tight approximate inference of logistic-normal admixture model
Amr Ahmed and Eric P. Xing
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


Generalized Non-metric Multidimensional Scaling
Sameer Agarwal, Josh Wills, Lawrence Cayton, Gert Lanckriet, David J. Kriegman and Serge Belongie
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


Policy-Gradients for PSRs and POMDPs
Douglas Aberdeen, Olivier Buffet and Owen Thomas
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007