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All publications at Proceedings of the 31st International Conference on Machine Learning (ICML-14)
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Relative Upper Confidence Bound for the K-Armed Dueling Bandit Problem
Masrour Zoghi, Shimon Whiteson, Remi Munos and Maarten D. Rijke
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Aggregating Ordinal Labels from Crowds by Minimax Conditional Entropy
Dengyong Zhou, Qiang Liu, John Platt and Christopher Meek
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Optimal PAC Multiple Arm Identification with Applications to Crowdsourcing
Yuan Zhou, Xi Chen and Jian Li
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Robust Principal Component Analysis with Complex Noise
Qian Zhao, Deyu Meng, Zongben Xu, Wangmeng Zuo and Lei Zhang
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Asynchronous Distributed ADMM for Consensus Optimization
Ruiliang Zhang and James Kwok
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Composite Quantization for Approximate Nearest Neighbor Search
Ting Zhang, Chao Du and Jingdong Wang
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Efficient Algorithms for Robust One-bit Compressive Sensing
Lijun Zhang, Jinfeng Yi and Rong Jin
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Saddle Points and Accelerated Perceptron Algorithms
Adams W. Yu, Fatma Kilinc-karzan and Jaime Carbonell
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Circulant Binary Embedding
Felix Yu, Sanjiv Kumar, Yunchao Gong and Shih-fu Chang
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Gradient Hard Thresholding Pursuit for Sparsity-Constrained Optimization
Xiaotong Yuan, Ping Li and Tong Zhang
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

A Single-Pass Algorithm for Efficiently Recovering Sparse Cluster Centers of High-dimensional Data
Jinfeng Yi, Lijun Zhang, Jun Wang, Rong Jin and Anil Jain
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Alternating Minimization for Mixed Linear Regression
Xinyang Yi, Constantine Caramanis and Sujay Sanghavi
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Optimization Equivalence of Divergences Improves Neighbor Embedding
Zhirong Yang, Jaakko Peltonen and Samuel Kaski
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Elementary Estimators for Sparse Covariance Matrices and other Structured Moments
Eunho Yang, Aurelie Lozano and Pradeep Ravikumar
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Elementary Estimators for High-Dimensional Linear Regression
Eunho Yang, Aurelie Lozano and Pradeep Ravikumar
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Coupled Group Lasso for Web-Scale CTR Prediction in Display Advertising
Ling Yan, Wu-jun Li, Gui-rong Xue and Dingyi Han
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Large-margin Weakly Supervised Dimensionality Reduction
Chang Xu, Dacheng Tao, Chao Xu and Yong Rui
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Large-margin Weakly Supervised Dimensionality Reduction
Chang Xu, Dacheng Tao, Chao Xu and Yong Rui
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Learning the Consistent Behavior of Common Users for Target Node Prediction across Social Networks
Shan-hung Wu, Hao-heng Chien, Kuan-hua Lin and Philip Yu
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Affinity Weighted Embedding
Jason Weston, Ron Weiss and Hector Yee
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Robust Learning under Uncertain Test Distributions: Relating Covariate Shift to Model Misspecification
Junfeng Wen, Chun-nam Yu and Russell Greiner
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Fast Multi-stage Submodular Maximization
Kai Wei, Rishabh Iyer and Jeff Bilmes
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Robust Distance Metric Learning via Simultaneous L1-Norm Minimization and Maximization
Hua Wang, Feiping Nie and Heng Huang
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Active Transfer Learning under Model Shift
Xuezhi Wang, Tzu-kuo Huang and Jeff Schneider
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Nonlinear Information-Theoretic Compressive Measurement Design
Liming Wang, Abolfazl Razi, Miguel Rodrigues, Robert Calderbank and Lawrence Carin
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Ensemble-Based Tracking: Aggregating Crowdsourced Structured Time Series Data
Naiyan Wang and Dit-yan Yeung
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Robust Inverse Covariance Estimation under Noisy Measurements
Jun-kun Wang and Shou-de Lin
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

The Falling Factorial Basis and Its Statistical Applications
Yu-xiang Wang, Alex Smola and Ryan Tibshirani
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Scaling SVM and Least Absolute Deviations via Exact Data Reduction
Jie Wang, Peter Wonka and Jieping Ye
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Two-Stage Metric Learning
Jun Wang, Ke Sun, Fei Sha, Stéphane Marchand-maillet and Alexandros Kalousis
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

A Highly Scalable Parallel Algorithm for Isotropic Total Variation Models
Jie Wang, Qingyang Li, Sen Yang, Wei Fan, Peter Wonka and Jieping Ye
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Rank-One Matrix Pursuit for Matrix Completion
Zheng Wang, Ming-jun Lai, Zhaosong Lu, Wei Fan, Hasan Davulcu and Jieping Ye
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

K-means recovers ICA filters when independent components are sparse
Alon Vinnikov and Shai Shalev-shwartz
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Spectral Bandits for Smooth Graph Functions
Michal Valko, Remi Munos, Branislav Kveton and Tomáš Kocák
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Making Fisher Discriminant Analysis Scalable
Bojun Tu, Zhihua Zhang, Shusen Wang and Hui Qian
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

A Deep Semi-NMF Model for Learning Hidden Representations
George Trigeorgis, Konstantinos Bousmalis, Stefanos Zafeiriou and Bjoern Schuller
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Statistical analysis of stochastic gradient methods for generalized linear models
Panagiotis Toulis, Edoardo Airoldi and Jason Rennie
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Lower Bounds for the Gibbs Sampler over Mixtures of Gaussians
Christopher Tosh and Sanjoy Dasgupta
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

On Robustness and Regularization of Structural Support Vector Machines
Mohamad A. Torkamani and Daniel Lowd
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Doubly Stochastic Variational Bayes for non-Conjugate Inference
Michalis Titsias and Miguel Lázaro-gredilla
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

GeNGA: A Generalization of Natural Gradient Ascent with Positive and Negative Convergence Results
Philip Thomas
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Local Ordinal Embedding
Yoshikazu Terada and Ulrike V. Luxburg
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

An Analysis of State-Relevance Weights and Sampling Distributions on L1-Regularized Approximate Linear Programming Approximation Accuracy
Gavin Taylor, Connor Geer and David Piekut
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Riemannian Pursuit for Big Matrix Recovery
Mingkui Tan, Ivor W. Tsang, Li Wang, Bart Vandereycken and Sinno J. Pan
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Scaling Up Robust MDPs using Function Approximation
Aviv Tamar, Shie Mannor and Huan Xu
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Outlier Path: A Homotopy Algorithm for Robust SVM
Shinya Suzumura, Kohei Ogawa, Masashi Sugiyama and Ichiro Takeuchi
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

A new Q(lambda) with interim forward view and Monte Carlo equivalence
Rich Sutton, Ashique R. Mahmood, Doina Precup and Hado V. Hasselt
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

A Convergence Rate Analysis for LogitBoost, MART and Their Variant
Peng Sun, Tong Zhang and Jie Zhou
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Learning Mixtures of Linear Classifiers
Yuekai Sun, Stratis Ioannidis and Andrea Montanari
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

An Information Geometry of Statistical Manifold Learning
Ke Sun and Stéphane Marchand-maillet
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Structured Prediction of Network Response
Hongyu Su, Aristides Gionis and Juho Rousu
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Jacob Steinhardt and Percy Liang
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

On learning to localize objects with minimal supervision
Hyun O. Song, Ross Girshick, Stefanie Jegelka, Julien Mairal, Zaid Harchaoui and Trevor Darrell
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Nonparametric Estimation of Multi-View Latent Variable Models
Le Song, Animashree Anandkumar, Bo Dai and Bo Xie
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Fast large-scale optimization by unifying stochastic gradient and quasi-Newton methods
Jascha Sohl-dickstein, Ben Poole and Surya Ganguli
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Input Warping for Bayesian Optimization of Non-Stationary Functions
Jasper Snoek, Kevin Swersky, Rich Zemel and Ryan Adams
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Near-Optimally Teaching the Crowd to Classify
Adish Singla, Ilija Bogunovic, Gabor Bartok, Amin Karbasi and Andreas Krause
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Active Learning of Parameterized Skills
Bruno D. Silva, George Konidaris and Andrew Barto
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Communication-Efficient Distributed Optimization using an Approximate Newton-type Method
Ohad Shamir, Nati Srebro and Tong Zhang
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

One Practical Algorithm for Both Stochastic and Adversarial Bandits
Yevgeny Seldin and Aleksandrs Slivkins
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Dino Sejdinovic, Heiko Strathmann, Maria L. Garcia, Christophe Andrieu and Arthur Gretton
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Globally Convergent Parallel MAP LP Relaxation Solver using the Frank-Wolfe Algorithm
Alexander Schwing, Tamir Hazan, Marc Pollefeys and Raquel Urtasun
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

A Physics-Based Model Prior for Object-Oriented MDPs
Jonathan Scholz, Martin Levihn, Charles Isbell and David Wingate
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Programming by Feedback
Marc Schoenauer, Riad Akrour, Michele Sebag and Jean-christophe Souplet
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Approximate Policy Iteration Schemes: A Comparison
Bruno Scherrer
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Latent Confusion Analysis by Normalized Gamma Construction
Issei Sato, Hisashi Kashima and Hiroshi Nakagawa
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Approximation Analysis of Stochastic Gradient Langevin Dynamics by using Fokker-Planck Equation and Ito Process
Issei Sato and Hiroshi Nakagawa
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Learning Character-level Representations for Part-of-Speech Tagging
Cicero D. Santos and Bianca Zadrozny
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Standardized Mutual Information for Clustering Comparisons: One Step Further in Adjustment for Chance
Simone Romano, James Bailey, Vinh Nguyen and Karin Verspoor
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Gaussian Process Classification and Active Learning with Multiple Annotators
Filipe Rodrigues, Francisco Pereira and Bernardete Ribeiro
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Learning Ordered Representations with Nested Dropout
Oren Rippel, Michael Gelbart and Ryan Adams
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Stochastic Backpropagation and Approximate Inference in Deep Generative Models
Danilo J. Rezende, Shakir Mohamed and Daan Wierstra
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Sparse meta-Gaussian information bottleneck
Melani Rey, Volker Roth and Thomas Fuchs
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Learning to Disentangle Factors of Variation with Manifold Interaction
Scott Reed, Kihyuk Sohn, Yuting Zhang and Honglak Lee
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Min-Max Problems on Factor Graphs
Siamak Ravanbakhsh, Christopher Srinivasa, Brendan Frey and Russell Greiner
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Scalable Bayesian Low-Rank Decomposition of Incomplete Multiway Tensors
Piyush Rai, Yingjian Wang, Shengbo Guo, Gary Chen, David Dunson and Lawrence Carin
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Spectral Regularization for Max-Margin Sequence Tagging
Ariadna Quattoni, Borja Balle, Xavier Carreras and Amir Globerson
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Sparse Reinforcement Learning via Convex Optimization
Zhiwei Qin, Weichang Li and Firdaus Janoos
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Marginal Structured SVM with Hidden Variables
Wei Ping, Qiang Liu and Alex Ihler
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

A PAC-Bayesian bound for Lifelong Learning
Anastasia Pentina and Christoph Lampert
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Finding Dense Subgraphs via Low-Rank Bilinear Optimization
Dimitris Papailiopoulos, Ioannis Mitliagkas, Alexandros Dimakis and Constantine Caramanis
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Learning by Stretching Deep Networks
Gaurav Pandey and Ambedkar Dukkipati
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

A Compilation Target for Probabilistic Programming Languages
Brooks Paige and Frank Wood
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Preserving Modes and Messages via Diverse Particle Selection
Jason Pacheco, Silvia Zuffi, Michael Black and Erik Sudderth
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Putting MRFs on a Tensor Train
Alexander Novikov, Anton Rodomanov, Anton Osokin and Dmitry Vetrov
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Transductive Learning with Multi-class Volume Approximation
Gang Niu, Bo Dai, Christoffel D. Plessis and Masashi Sugiyama
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Exchangeable Variable Models
Mathias Niepert and Pedro Domingos
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Optimal Mean Robust Principal Component Analysis
Feiping Nie, Jianjun Yuan and Heng Huang
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Linear Time Solver for Primal SVM
Feiping Nie, Yizhen Huang and Heng Huang
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Multivariate Maximal Correlation Analysis
Hoang V. Nguyen, Emmanuel Müller, Jilles Vreeken, Pavel Efros and Klemens Böhm
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Model-Based Relational RL When Object Existence is Partially Observable
Vien Ngo and Marc Toussaint
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Adaptive Monte Carlo via Bandit Allocation
James Neufeld, Andras Gyorgy, Csaba Szepesvari and Dale Schuurmans
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Rectangular Tiling Process
Masahiro Nakano, Katsuhiko Ishiguro, Akisato Kimura, Takeshi Yamada and Naonori Ueda
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Probabilistic Partial Canonical Correlation Analysis
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Square Deal: Lower Bounds and Improved Relaxations for Tensor Recovery
Cun Mu, Bo Huang, John Wright and Donald Goldfarb
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Neural Variational Inference and Learning in Belief Networks
Andriy Mnih and Karol Gregor
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Linear and Parallel Learning of Markov Random Fields
Yariv Mizrahi, Misha Denil and Nando D. Freitas
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Structured Recurrent Temporal Restricted Boltzmann Machines
Roni Mittelman, Benjamin Kuipers, Silvio Savarese and Honglak Lee
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Scalable and Robust Bayesian Inference via the Median Posterior
Stanislav Minsker, Sanvesh Srivastava, Lizhen Lin and David Dunson
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Learning Latent Variable Gaussian Graphical Models
Zhaoshi Meng, Brian Eriksson and Al Hero
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Improving offline evaluation of contextual bandit algorithms via bootstrapping techniques
Jérémie Mary, Philippe Preux and Olivier Nicol
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Time-Regularized Interrupting Options (TRIO)
Timothy Mann, Daniel Mankowitz and Shie Mannor
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Convex Total Least Squares
Dmitry Malioutov and Nikolai Slavov
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Linear Programming for Large-Scale Markov Decision Problems
Alan Malek, Yasin Abbasi-yadkori and Peter Bartlett
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Structured Generative Models of Natural Source Code
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Randomized Nonlinear Component Analysis
David Lopez-paz, Suvrit Sra, Alex Smola, Zoubin Ghahramani and Bernhard Schoelkopf
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Randomized Nonlinear Component Analysis
David Lopez-paz, Suvrit Sra, Alex Smola, Zoubin Ghahramani and Bernhard Schoelkopf
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Learnability of the Superset Label Learning Problem
Liping Liu and Thomas Dietterich
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Gaussian Approximation of Collective Graphical Models
Liping Liu, Daniel Sheldon and Thomas Dietterich
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Multiple Testing under Dependence via Semiparametric Graphical Models
Jie Liu, Chunming Zhang, Elizabeth Burnside and David Page
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

An Asynchronous Parallel Stochastic Coordinate Descent Algorithm
Ji Liu, Steve Wright, Christopher Re, Victor Bittorf and Srikrishna Sridhar
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Safe Screening with Variational Inequalities and Its Application to Lasso
Jun Liu, Zheng Zhao, Jie Wang and Jieping Ye
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Stable and Efficient Representation Learning with Nonnegativity Constraints
Tsung-han Lin and H. T. Kung
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Discovering Latent Network Structure in Point Process Data
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Combinatorial Partial Monitoring Game with Linear Feedback and Its Applications
Tian Lin, Bruno Abrahao, Robert Kleinberg, John Lui and Wei Chen
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Multi-label Classification via Feature-aware Implicit Label Space Encoding
Zijia Lin, Guiguang Ding, Mingqing Hu and Jianmin Wang
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Geodesic Distance Function Learning via Heat Flow on Vector Fields
Binbin Lin, Ji Yang, Xiaofei He and Jieping Ye
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Efficient Learning of Mahalanobis Metrics for Ranking
Daryl Lim and Gert Lanckriet
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

High Order Regularization for Semi-Supervised Learning of Structured Output Problems
Yujia Li and Rich Zemel
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Coding for Random Projections
Ping Li, Michael Mitzenmacher and Anshumali Shrivastava
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Latent Semantic Representation Learning for Scene Classification
Xin Li and Yuhong Guo
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Bayesian Max-margin Multi-Task Learning with Data Augmentation
Chengtao Li, Jun Zhu and Jianfei Chen
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Learning Complex Neural Network Policies with Trajectory Optimization
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Dynamic Programming Boosting for Discriminative Macro-Action Discovery
Leonidas Lefakis and Francois Fleuret
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Distributed Representations of Sentences and Documents
Quoc Le and Tomas Mikolov
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Distributed Representations of Sentences and Documents
Quoc Le and Tomas Mikolov
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Stochastic Neighbor Compression
Matt Kusner, Stephen Tyree, Kilian Q. Weinberger and Kunal Agrawal
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

The f-Adjusted Graph Laplacian: a Diagonal Modification with a Geometric Interpretation
Sven Kurras, Ulrike V. Luxburg and Gilles Blanchard
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Nonparametric Estimation of Renyi Divergence and Friends
Akshay Krishnamurthy, Kirthevasan Kandasamy, Barnabas Poczos and Larry Wasserman
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

On the convergence of no-regret learning in selfish routing
Walid Krichene, Benjamin Drighès and Alexandre Bayen
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Consistency of Causal Inference under the Additive Noise Model
Samory Kpotufe, Eleni Sgouritsa, Dominik Janzing and Bernhard Schoelkopf
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

A Clockwork RNN
Jan Koutnik, Klaus Greff, Faustino Gomez and Juergen Schmidhuber
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Maximum Margin Multiclass Nearest Neighbors
Aryeh Kontorovich and Roi Weiss
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Concentration in unbounded metric spaces and algorithmic stability
Aryeh Kontorovich
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Multiresolution Matrix Factorization
Risi Kondor, Nedelina Teneva and Vikas Garg
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

A reversible infinite HMM using normalised random measures
David Knowles, Zoubin Ghahramani and Konstantina Palla
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Multimodal Neural Language Models
Ryan Kiros, Ruslan Salakhutdinov and Rich Zemel
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Efficient Gradient-Based Inference through Transformations between Bayes Nets and Neural Nets
Diederik Kingma and Max Welling
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Hierarchical Dirichlet Scaling Process
Dongwoo Kim and Alice Oh
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Hard-Margin Active Linear Regression
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Memory (and Time) Efficient Sequential Monte Carlo
Seong-hwan Jun and Alexandre Bouchard-côté
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Stochastic Variational Inference for Bayesian Time Series Models
Matthew Johnson and Alan Willsky
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Global graph kernels using geometric embeddings
Fredrik Johansson, Vinay Jethava, Devdatt Dubhashi and Chiranjib Bhattacharyya
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

On p-norm Path Following in Multiple Kernel Learning for Non-linear Feature Selection
Pratik Jawanpuria, Manik Varma and Saketha Nath
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Scalable Semidefinite Relaxation for Maximum A Posterior Estimation
Qixing Huang, Yuxin Chen and Leonidas Guibas
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Multi-period Trading Prediction Markets with Connections to Machine Learning
Jinli Hu and Amos Storkey
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Heavy-tailed regression with a generalized median-of-means
Daniel Hsu and Sivan Sabato
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Cold-start Active Learning with Robust Ordinal Matrix Factorization
Neil Houlsby, Jose M. Hernandez-lobato and Zoubin Ghahramani
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

A Unified Framework for Consistency of Regularized Loss Minimizers
Jean Honorio and Tommi Jaakkola
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Nonmyopic $\epsilon$-Bayes-Optimal Active Learning of Gaussian Processes
Trong N. Hoang, Bryan Low, Patrick Jaillet and Mohan Kankanhalli
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Probabilistic Matrix Factorization with Non-random Missing Data
Jose M. Hernandez-lobato, Neil Houlsby and Zoubin Ghahramani
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Stochastic Inference for Scalable Probabilistic Modeling of Binary Matrices
Jose M. Hernandez-lobato, Neil Houlsby and Zoubin Ghahramani
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Inferning with High Girth Graphical Models
Uri Heinemann and Amir Globerson
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Beta Diffusion Trees
Creighton Heaukulani, David Knowles and Zoubin Ghahramani
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Concept Drift Detection Through Resampling
Maayan Harel, Shie Mannor, Ran El-yaniv and Koby Crammer
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Compact Random Feature Maps
Raffay Hamid, Ying Xiao, Alex Gittens and Dennis Decoste
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Structured Low-Rank Matrix Factorization: Optimality, Algorithm, and Applications to Image Processing
Benjamin Haeffele, Eric Young and Rene Vidal
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Exponential Family Matrix Completion under Structural Constraints
Suriya Gunasekar, Pradeep Ravikumar and Joydeep Ghosh
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Deep AutoRegressive Networks
Karol Gregor, Ivo Danihelka, Andriy Mnih, Charles Blundell and Daan Wierstra
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Towards End-To-End Speech Recognition with Recurrent Neural Networks
Alex Graves and Navdeep Jaitly
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Sample Efficient Reinforcement Learning with Gaussian Processes
Robert Grande, Thomas Walsh and Jonathan How
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Anti-differentiating approximation algorithms:A case study with min-cuts, spectral, and flow
David Gleich and Michael Mahoney
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Robust and Efficient Kernel Hyperparameter Paths with Guarantees
Joachim Giesen, Soeren Laue and Patrick Wieschollek
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Online Clustering of Bandits
Claudio Gentile, Shuai Li and Giovanni Zappella
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Bayesian Optimization with Inequality Constraints
Jacob Gardner, Matt Kusner, Kilian Q. Weinberger, John Cunningham and Zhixiang Xu
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Pitfalls in the use of Parallel Inference for the Dirichlet Process
Yarin Gal and Zoubin Ghahramani
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Dual Query: Practical Private Query Release for High Dimensional Data
Marco Gaboardi, Emilio Arias, Justin Hsu, Aaron Roth and Zhiwei S. Wu
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Efficient Label Propagation
Yasuhiro Fujiwara and Go Irie
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Graph-based Semi-supervised Learning: Realizing Pointwise Smoothness Probabilistically
Yuan Fang, Kevin Chang and Hady Lauw
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Signal recovery from Pooling Representations
Joan B. Estrach, Arthur Szlam and Yann Lecun
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Discrete Chebyshev Classifiers
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Pursuit-Evasion Without Regret, with an Application to Trading
Lili Dworkin, Michael Kearns and Yuriy Nevmyvaka
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Influence Function Learning in Information Diffusion Networks
Nan Du, Yingyu Liang, Le Song and Maria-Florina Balcan
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Finito: A faster, permutable incremental gradient method for big data problems
Aaron Defazio, Justin Domke and Tiberio Caetano
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Automated inference of point of view from user interactions in collective intelligence venues
Sanmay Das and Allen Lavoie
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Estimating Diffusion Network Structures: Recovery Conditions, Sample Complexity & Soft-thresholding Algorithm
Hadi Daneshmand, Manuel Gomez-rodriguez, Le Song and Bernhard Schoelkopf
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Fast Computation of Wasserstein Barycenters
Marco Cuturi and Arnaud Doucet
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Deep Boosting
Corinna Cortes, Mehryar Mohri and Umar Syed
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Ensemble Methods for Structured Prediction
Corinna Cortes, Vitaly Kuznetsov and Mehryar Mohri
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Gaussian Process Optimization with Mutual Information
Emile Contal, Vianney Perchet and Nicolas Vayatis
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Learning the Irreducible Representations of Commutative Lie Groups
Taco Cohen and Max Welling
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Anomaly Ranking as Supervised Bipartite Ranking
Stephan Clémençon and Sylvain Robbiano
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

A Kernel Independence Test for Random Processes
Kacper Chwialkowski and Arthur Gretton
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Nearest Neighbors Using Compact Sparse Codes
Anoop Cherian
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Tianqi Chen, Emily Fox and Carlos Guestrin
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Weighted Graph Clustering with Non-Uniform Uncertainties
Yudong Chen, Shiau H. Lim and Huan Xu
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Marginalized Denoising Auto-encoders for Nonlinear Representations
Minmin Chen, Kilian Q. Weinberger, Fei Sha and Yoshua Bengio
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Topic Modeling using Topics from Many Domains, Lifelong Learning and Big Data
Zhiyuan Chen and Bing Liu
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Statistical-Computational Phase Transitions in Planted Models: The High-Dimensional Setting
Yudong Chen and Jiaming Xu
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Near-Optimal Joint Object Matching via Convex Relaxation
Yuxin Chen, Leonidas Guibas and Qixing Huang
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Effective Bayesian Modeling of Groups of Related Count Time Series
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Estimating Latent-Variable Graphical Models using Moments and Likelihoods
Arun T. Chaganty and Percy Liang
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Deterministic Anytime Inference for Stochastic Continuous-Time Markov Processes
E. B. Celikkaya and Christian Shelton
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Efficient Dimensionality Reduction for High-Dimensional Network Estimation
Safiye Celik, Benjamin Logsdon and Su-in Lee
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Hierarchical Quasi-Clustering Methods for Asymmetric Networks
Gunnar Carlsson, Facundo Mémoli, Alejandro Ribeiro and Santiago Segarra
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Preference-Based Rank Elicitation using Statistical Models: The Case of Mallows
Robert Busa-fekete, Eyke Huellermeier and Balázs Szörényi
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

PAC-inspired Option Discovery in Lifelong Reinforcement Learning
Emma Brunskill and Lihong Li
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Scalable Gaussian Process Structured Prediction for Grid Factor Graph Applications
Sebastien Bratieres, Novi Quadrianto, Sebastian Nowozin and Zoubin Ghahramani
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Compositional Morphology for Word Representations and Language Modelling
Jan Botha and Phil Blunsom
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Universal Matrix Completion
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Deep Generative Stochastic Networks Trainable by Backprop
Yoshua Bengio, Eric Laufer, Guillaume Alain and Jason Yosinski
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

A Bayesian Wilcoxon signed-rank test based on the Dirichlet process
Alessio Benavoli, Giorgio Corani, Francesca Mangili, Marco Zaffalon and Fabrizio Ruggeri
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Clustering in the Presence of Background Noise
Shai Ben-david and Nika Haghtalab
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Skip Context Tree Switching
Marc Bellemare, Joel Veness and Erik Talvitie
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Guess-Averse Loss Functions For Cost-Sensitive Multiclass Boosting
Oscar Beijbom, Mohammad Saberian, David Kriegman and Nuno Vasconcelos
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Variational Inference for Sequential Distance Dependent Chinese Restaurant Process
Sergey Bartunov and Dmitry Vetrov
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Gaussian Processes for Bayesian Estimation in Ordinary Differential Equations
David Barber and Yali Wang
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Methods of Moments for Learning Stochastic Languages: Unified Presentation and Empirical Comparison
Borja Balle, William Hamilton and Joelle Pineau
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

A Bayesian Framework for Online Classifier Ensemble
Qinxun Bai, Henry Lam and Stan Sclaroff
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Sample-based approximate regularization
Philip Bachman, Amir-massoud Farahmand and Doina Precup
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Learning Modular Structures from Network Data and Node Variables
Elham Azizi, Edoardo Airoldi and James Galagan
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Online Stochastic Optimization under Correlated Bandit Feedback
Mohammad G. Azar, Alessandro Lazaric and Emma Brunskill
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Local algorithms for interactive clustering
Pranjal Awasthi, Konstantin Voevodski and Maria-Florina Balcan
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Nonnegative Sparse PCA with Provable Guarantees
Megasthenis Asteris, Dimitris Papailiopoulos and Alexandros Dimakis
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

A Unifying View of Representer Theorems
Andreas Argyriou and Francesco Dinuzzo
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Learning Polynomials with Neural Networks
Alexandr Andoni, Rina Panigrahy, Gregory Valiant and Li Zhang
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Memory and Computation Efficient PCA via Very Sparse Random Projections
Farhad P. Anaraki and Shannon Hughes
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Haitham B. Ammar, Eric Eaton, Paul Ruvolo and Matthew Taylor
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Learning from Contagion (Without Timestamps)
Kareem Amin, Hoda Heidari and Michael Kearns
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Reducing Dueling Bandits to Cardinal Bandits
Nir Ailon, Zohar Karnin and Thorsten Joachims
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Sungjin Ahn, Babak Shahbaba and Max Welling
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Hierarchical Conditional Random Fields for Outlier Detection: An Application tahmed14.pdfo Detecting Epileptogenic Cortical Malformations
Bilal Ahmed, Thomas Thesen, Karen Blackmon, Yijun Zhao, Orrin Devinsky, Ruben Kuzniecky and Carla Brodley
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

GEV-Canonical Regression for Accurate Binary Class Probability Estimation when Onagarwalc14.pdfe Class is Rare
Arpit Agarwal, Harikrishna Narasimhan, Shivaram Kalyanakrishnan and Shivani Agarwal
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Taming the Monster: A Fast and Simple Algorithm for Contextual Bandits
Alekh Agarwal, Daniel Hsu, Satyen Kale, John Langford, Lihong Li and Robert Schapire
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Least Squares Revisited: Scalable Approaches for Multi-class Prediction
Alekh Agarwal, Sham Kakade, Nikos Karampatziakis, Le Song and Gregory Valiant
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Learning the Parameters of Determinantal Point Process Kernels
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Deep Supervised and Convolutional Generative Stochastic Network for Protein Secondary Structure Prediction
Jian Zhou and Olga Troyanskaya
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Fast Stochastic Alternating Direction Method of Multipliers
Wenliang Zhong and James Kwok
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Max-Margin Infinite Hidden Markov Models
Aonan Zhang, Jun Zhu and Bo Zhang
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Covering Number for Efficient Heuristic-based POMDP Planning
Zongzhang Zhang, David Hsu and Wee S. Lee
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Large-scale Multi-label Learning with Missing Labels
Hsiang-fu Yu, Prateek Jain, Purushottam Kar and Inderjit Dhillon
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Making the Most of Bag of Words: Sentence Regularization with Alternating Direction Method of Multipliers
Dani Yogatama and Noah Smith
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Quasi-Monte Carlo Feature Maps for Shift-Invariant Kernels
Jiyan Yang, Vikas Sindhwani, Haim Avron and Michael Mahoney
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

The Coherent Loss Function for Classification
Wenzhuo Yang, Melvyn Sim and Huan Xu
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

A Deep and Tractable Density Estimator
Benigno Uria, Iain Murray and Hugo Larochelle
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Bias in Natural Actor-Critic Algorithms
Philip Thomas
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Understanding the Limiting Factors of Topic Modeling via Posterior Contraction Analysis
Jian Tang, Zhaoshi Meng, Xuanlong Nguyen, Qiaozhu Mei and Ming Zhang
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Learning Graphs with a Few Hubs
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Boosting multi-step autoregressive forecasts
Souhaib B. Taieb and Rob Hyndman
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Stochastic Dual Coordinate Ascent with Alternating Direction Method of Multipliers
Taiji Suzuki
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Filtering with Abstract Particles
Jacob Steinhardt and Percy Liang
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Demystifying Information-Theoretic Clustering
Greg V. Steeg, Aram Galstyan, Fei Sha and Simon Dedeo
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Computing Parametric Ranking Models via Rank-Breaking
Hossein A. Soufiani, David Parkes and Lirong Xia
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Optimal Budget Allocation: Theoretical Guarantee and Efficient Algorithm
Tasuku Soma, Naonori Kakimura, Kazuhiro Inaba and Ken-ichi Kawarabayashi
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Wasserstein Propagation for Semi-Supervised Learning
Justin Solomon, Raif Rustamov, Guibas Leonidas and Adrian Butscher
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Hamiltonian Monte Carlo Without Detailed Balance
Jascha Sohl-dickstein, Mayur Mudigonda and Michael Deweese
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Generalized Exponential Concentration Inequality for Renyi Divergence Estimation
Shashank Singh and Barnabas Poczos
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

David Silver, Guy Lever, Nicolas Heess, Thomas Degris, Daan Wierstra and Martin Riedmiller
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Memory Efficient Kernel Approximation
Si Si, Cho-jui Hsieh and Inderjit Dhillon
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Densifying One Permutation Hashing via Rotation for Fast Near Neighbor Search
Anshumali Shrivastava and Ping Li
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Online Bayesian Passive-Aggressive Learning
Tianlin Shi and Jun Zhu
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Coordinate-descent for learning orthogonal matrices through Givens rotations
Uri Shalit and Gal Chechik
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Accelerated Proximal Stochastic Dual Coordinate Ascent for Regularized Loss Minimization
Shai Shalev-shwartz and Tong Zhang
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Prediction with Limited Advice and Multiarmed Bandits with Paid Observations
Yevgeny Seldin, Peter Bartlett, Koby Crammer and Yasin Abbasi-yadkori
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

True Online TD(lambda)
Harm V. Seijen and Rich Sutton
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

A Discriminative Latent Variable Model for Online Clustering
Rajhans Samdani, Kai-wei Chang and Dan Roth
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Learning Sum-Product Networks with Direct and Indirect Variable Interactions
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Margins, Kernels and Non-linear Smoothed Perceptrons
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

A Statistical Convergence Perspective of Algorithms for Rank Aggregation from Pairwise Data
Arun Rajkumar and Shivani Agarwal
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

The Inverse Regression Topic Model
Maxim Rabinovich and David Blei
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Recurrent Convolutional Neural Networks for Scene Labeling
Pedro Pinheiro and Ronan Collobert
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

On Measure Concentration of Random Maximum A-Posteriori Perturbations
Francesco Orabona, Tamir Hazan, Anand Sarwate and Tommi Jaakkola
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Bayesian Nonparametric Multilevel Clustering with Group-Level Contexts
Tien V. Nguyen, Dinh Phung, Xuanlong Nguyen, Swetha Venkatesh and Hung Bui
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Fast Allocation of Gaussian Process Experts
Trung Nguyen and Edwin Bonilla
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Kernel Mean Estimation and Stein Effect
Krikamol Muandet, Kenji Fukumizu, Bharath Sriperumbudur, Arthur Gretton and Bernhard Schölkopf
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Factorized Point Process Intensities: A Spatial Analysis of Professional Basketball
Andrew Miller, Luke Bornn, Ryan Adams and Kirk Goldsberry
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Robust RegBayes: Selectively Incorporating First-Order Logic Domain Knowledge into Bayesian Models
Shike Mei, Jun Zhu and Jerry Zhu
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Learning Theory and Algorithms for revenue optimization in second price auctions with reserve
Andres M. Medina and Mehryar Mohri
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Scaling Up Approximate Value Iteration with Options: Better Policies with Fewer Iterations
Timothy Mann and Shie Mannor
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Latent Bandits.
Odalric-ambrym Maillard and Shie Mannor
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

A Statistical Perspective on Algorithmic Leveraging
Ping Ma, Michael Mahoney and Bin Yu
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Towards Minimax Online Learning with Unknown Time Horizon
Haipeng Luo and Robert Schapire
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Forward-Backward Greedy Algorithms for General Convex Smooth Functions over A Cardinality Constraint
Ji Liu, Jieping Ye and Ryohei Fujimaki
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Efficient Approximation of Cross-Validation for Kernel Methods using Bouligand Influence Function
Yong Liu, Shali Jiang and Shizhong Liao
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

An Adaptive Accelerated Proximal Gradient Method and its Homotopy Continuation for Sparse Optimization
Qihang Lin and Lin Xiao
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

On Modelling Non-linear Topical Dependencies
Zhixing Li, Siqiang Wen, Juanzi Li, Peng Zhang and Jie Tang
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Modeling Correlated Arrival Events with Latent Semi-Markov Processes
Wenzhao Lian, Vinayak Rao, Brian Eriksson and Lawrence Carin
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Condensed Filter Tree for Cost-Sensitive Multi-Label Classification
Chun-liang Li and Hsuan-tien Lin
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Latent Variable Copula Inference for Bundle Pricing from Retail Transaction Data
Benjamin Letham, Wei Sun and Anshul Sheopuri
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Spherical Hamiltonian Monte Carlo for Constrained Target Distributions
Shiwei Lan, Bo Zhou and Babak Shahbaba
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Large-Margin Metric Learning for Constrained Partitioning Problems
Rémi Lajugie, Francis Bach and Sylvain Arlot
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Agnostic Bayesian Learning of Ensembles
Alexandre Lacoste, Mario Marchand, François Laviolette and Hugo Larochelle
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Austerity in MCMC Land: Cutting the Metropolis-Hastings Budget
Anoop Korattikara, Yutian Chen and Max Welling
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Asymptotically consistent estimation of the number of change points in highly dependent time series
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Discriminative Features via Generalized Eigenvectors
Nikos Karampatziakis and Paul Mineiro
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

(Near) Dimension Independent Risk Bounds for Differentially Private Learning
Prateek Jain and Abhradeep G. Thakurta
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Maximum Mean Discrepancy for Class Ratio Estimation: Convergence Bounds and Kernel Selection
Arun Iyer, Saketha Nath and Sunita Sarawagi
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Admixture of Poisson MRFs: A Topic Model with Word Dependencies
David Inouye, Pradeep Ravikumar and Inderjit Dhillon
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

An Efficient Approach for Assessing Hyperparameter Importance
Frank Hutter, Holger Hoos and Kevin Leyton-brown
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Nuclear Norm Minimization via Active Subspace Selection
Cho-jui Hsieh and Peder Olsen
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

A Divide-and-Conquer Solver for Kernel Support Vector Machines
Cho-jui Hsieh, Si Si and Inderjit Dhillon
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Efficient Continuous-Time Markov Chain Estimation
Monir Hajiaghayi, Bonnie Kirkpatrick, Liangliang Wang and Alexandre Bouchard-côté
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Thompson Sampling for Complex Online Problems
Aditya Gopalan, Shie Mannor and Yishay Mansour
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Von Mises-Fisher Clustering Models
Siddharth Gopal and Yiming Yang
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Buffer k-d Trees: Processing Massive Nearest Neighbor Queries on GPUs
Fabian Gieseke, Justin Heinermann, Cosmin Oancea and Christian Igel
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Low-density Parity Constraints for Hashing-Based Discrete Integration
Stefano Ermon, Carla Gomes, Ashish Sabharwal and Bart Selman
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

DeCAF: A Deep Convolutional Activation Feature for Generic Visual Recognition
Jeff Donahue, Yangqing Jia, Oriol Vinyals, Judy Hoffman, Ning Zhang, Eric Tzeng and Trevor Darrell
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Online Learning in Markov Decision Processes with Changing Cost Sequences
Travis Dick, Andras Gyorgy and Csaba Szepesvari
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Dimension-free Concentration Bounds on Hankel Matrices for Spectral Learning
François Denis, Mattias Gybels and Amaury Habrard
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Narrowing the Gap: Random Forests In Theory and In Practice
Misha Denil, David Matheson and Nando D. Freitas
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Unimodal Bandits: Regret Lower Bounds and Optimal Algorithms
Richard Combes and Alexandre Proutiere
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Diagnosis determination: decision trees optimizing simultaneously worst and expected testing cost
Ferdinando Cicalese, Eduardo Laber and Aline M. Saettler
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Coherent Matrix Completion
Yudong Chen, Srinadh Bhojanapalli, Sujay Sanghavi and Rachel Ward
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Boosting with Online Binary Learners for the Multiclass Bandit Problem
Shang-tse Chen, Hsuan-tien Lin and Chi-jen Lu
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Yuxin Chen, Hiroaki Shioi, Cesar F. Montesinos, Lian P. Koh, Serge Wich and Andreas Krause
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Convergence rates for persistence diagram estimation in Topological Data Analysis
Frédéric Chazal, Marc Glisse, Catherine Labruère and Bertrand Michel
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

A Consistent Histogram Estimator for Exchangeable Graph Models
Stanley Chan and Edoardo Airoldi
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Towards scaling up Markov chain Monte Carlo: an adaptive subsampling approach
Rémi Bardenet, Arnaud Doucet and Chris Holmes
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014

Towards an optimal stochastic alternating direction method of multipliers