Volume 38: Artificial Intelligence and Statistics, 9-12 May 2015, San Diego, California, USA

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Editors: Guy Lebanon, S. V. N. Vishwanathan

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Nonparametric Bayesian Factor Analysis for Dynamic Count Matrices

Ayan Acharya, Joydeep Ghosh, Mingyuan Zhou ; PMLR 38:1-9

Parameter Estimation of Generalized Linear Models without Assuming their Link Function

Sreangsu Acharyya, Joydeep Ghosh ; PMLR 38:10-18

Spectral Gap Error Bounds for Improving CUR Matrix Decomposition and the Nyström Method

David Anderson, Simon Du, Michael Mahoney, Christopher Melgaard, Kunming Wu, Ming Gu ; PMLR 38:19-27

Global Multi-armed Bandits with Hölder Continuity

Onur Atan, Cem Tekin, Mihaela Schaar ; PMLR 38:28-36

Efficient Sparse Clustering of High-Dimensional Non-spherical Gaussian Mixtures

Martin Azizyan, Aarti Singh, Larry Wasserman ; PMLR 38:37-45

Unifying Local Consistency and MAX SAT Relaxations for Scalable Inference with Rounding Guarantees

Stephen Bach, Bert Huang, Lise Getoor ; PMLR 38:46-55

Near-optimal max-affine estimators for convex regression

Gabor Balazs, András György, Csaba Szepesvari ; PMLR 38:56-64

Convex Multi-Task Learning by Clustering

Aviad Barzilai, Koby Crammer ; PMLR 38:65-73

Gaussian Processes for Bayesian hypothesis tests on regression functions

Alessio Benavoli, Francesca Mangili ; PMLR 38:74-82

Sparse Solutions to Nonnegative Linear Systems and Applications

Aditya Bhaskara, Ananda Suresh, Morteza Zadimoghaddam ; PMLR 38:83-92

Generalized Linear Models for Aggregated Data

Avradeep Bhowmik, Joydeep Ghosh, Oluwasanmi Koyejo ; PMLR 38:93-101

Accurate and conservative estimates of MRF log-likelihood using reverse annealing

Yuri Burda, Roger Grosse, Ruslan Salakhutdinov ; PMLR 38:102-110

Stochastic Spectral Descent for Restricted Boltzmann Machines

David Carlson, Volkan Cevher, Lawrence Carin ; PMLR 38:111-119

Implementable confidence sets in high dimensional regression

Alexandra Carpentier ; PMLR 38:120-128

Online Ranking with Top-1 Feedback

Sougata Chaudhuri, Ambuj Tewari ; PMLR 38:129-137

One-bit Compressed Sensing with the k-Support Norm

Sheng Chen, Arindam Banerjee ; PMLR 38:138-146

Efficient Second-Order Gradient Boosting for Conditional Random Fields

Tianqi Chen, Sameer Singh, Ben Taskar, Carlos Guestrin ; PMLR 38:147-155

Filtered Search for Submodular Maximization with Controllable Approximation Bounds

Wenlin Chen, Yixin Chen, Kilian Weinberger ; PMLR 38:156-164

Predictive Inverse Optimal Control for Linear-Quadratic-Gaussian Systems

Xiangli Chen, Brian Ziebart ; PMLR 38:165-173

Exact Bayesian Learning of Ancestor Relations in Bayesian Networks

Yetian Chen, Lingjian Meng, Jin Tian ; PMLR 38:174-182

Model Selection for Topic Models via Spectral Decomposition

Dehua Cheng, Xinran He, Yan Liu ; PMLR 38:183-191

The Loss Surfaces of Multilayer Networks

Anna Choromanska, MIkael Henaff, Michael Mathieu, Gerard Ben Arous, Yann LeCun ; PMLR 38:192-204

Averaged Least-Mean-Squares: Bias-Variance Trade-offs and Optimal Sampling Distributions

Alexandre Defossez, Francis Bach ; PMLR 38:205-213

A Topic Modeling Approach to Ranking

Weicong Ding, Prakash Ishwar, Venkatesh Saligrama ; PMLR 38:214-222

A totally unimodular view of structured sparsity

Marwa El Halabi, Volkan Cevher ; PMLR 38:223-231

Back to the Past: Source Identification in Diffusion Networks from Partially Observed Cascades

Mehrdad Farajtabar, Manuel Gomez Rodriguez, Mohammad Zamani, Nan Du, Hongyuan Zha, Le Song ; PMLR 38:232-240

Graph Approximation and Clustering on a Budget

Ethan Fetaya, Ohad Shamir, Shimon Ullman ; PMLR 38:241-249

A Sufficient Statistics Construction of Exponential Family Le ́vy Measure Densities for Nonparametric Conjugate Models

Robert Finn, Brian Kulis ; PMLR 38:250-258

Computational Complexity of Linear Large Margin Classification With Ramp Loss

Søren Frejstrup Maibing, Christian Igel ; PMLR 38:259-267

Learning Deep Sigmoid Belief Networks with Data Augmentation

Zhe Gan, Ricardo Henao, David Carlson, Lawrence Carin ; PMLR 38:268-276

Efficient Estimation of Mutual Information for Strongly Dependent Variables

Shuyang Gao, Greg Ver Steeg, Aram Galstyan ; PMLR 38:277-286

On Anomaly Ranking and Excess-Mass Curves

Nicolas Goix, Anne Sabourin, Stéphan Clémençon ; PMLR 38:287-295

Modeling Skill Acquisition Over Time with Sequence and Topic Modeling

José González-Brenes ; PMLR 38:296-305

Consistent Collective Matrix Completion under Joint Low Rank Structure

Suriya Gunasekar, Makoto Yamada, Dawei Yin, Yi Chang ; PMLR 38:306-314

The Bayesian Echo Chamber: Modeling Social Influence via Linguistic Accommodation

Fangjian Guo, Charles Blundell, Hanna Wallach, Katherine Heller ; PMLR 38:315-323

Preserving Privacy of Continuous High-dimensional Data with Minimax Filters

Jihun Hamm ; PMLR 38:324-332

A Consistent Method for Graph Based Anomaly Localization

Satoshi Hara, Tetsuro Morimura, Toshihiro Takahashi, Hiroki Yanagisawa, Taiji Suzuki ; PMLR 38:333-341

Metric recovery from directed unweighted graphs

Tatsunori Hashimoto, Yi Sun, Tommi Jaakkola ; PMLR 38:342-350

Scalable Variational Gaussian Process Classification

James Hensman, Alexander Matthews, Zoubin Ghahramani ; PMLR 38:351-360

Stochastic Structured Variational Inference

Matthew Hoffman, David Blei ; PMLR 38:361-369

Reliable and Scalable Variational Inference for the Hierarchical Dirichlet Process

Michael Hughes, Dae Il Kim, Erik Sudderth ; PMLR 38:370-378

Cross-domain recommendation without shared users or items by sharing latent vector distributions

Tomoharu Iwata, Takeuchi Koh ; PMLR 38:379-387

Submodular Point Processes with Applications to Machine learning

Rishabh Iyer, Jeffrey Bilmes ; PMLR 38:388-397

Online Optimization : Competing with Dynamic Comparators

Ali Jadbabaie, Alexander Rakhlin, Shahin Shahrampour, Karthik Sridharan ; PMLR 38:398-406

Estimating the accuracies of multiple classifiers without labeled data

Ariel Jaffe, Boaz Nadler, Yuval Kluger ; PMLR 38:407-415

Sparse Dueling Bandits

Kevin Jamieson, Sumeet Katariya, Atul Deshpande, Robert Nowak ; PMLR 38:416-424

Consensus Message Passing for Layered Graphical Models

Varun Jampani, S. M. Ali Eslami, Daniel Tarlow, Pushmeet Kohli, John Winn ; PMLR 38:425-433

Robust Cost Sensitive Support Vector Machine

Shuichi Katsumata, Akiko Takeda ; PMLR 38:434-443

On Approximate Non-submodular Minimization via Tree-Structured Supermodularity

Yoshinobu Kawahara, Rishabh Iyer, Jeffrey Bilmes ; PMLR 38:444-452

Sparse Submodular Probabilistic PCA

Rajiv Khanna, Joydeep Ghosh, Russell Poldrack, Oluwasanmi Koyejo ; PMLR 38:453-461

Latent feature regression for multivariate count data

Arto Klami, Abhishek Tripathi, Johannes Sirola, Lauri Väre, Frederic Roulland ; PMLR 38:462-470

Dimensionality estimation without distances

Matthäus Kleindessner, Ulrike Luxburg ; PMLR 38:471-479

A Bayes consistent 1-NN classifier

Aryeh Kontorovich, Roi Weiss ; PMLR 38:480-488

DART: Dropouts meet Multiple Additive Regression Trees

Rashmi Korlakai Vinayak, Ran Gilad-Bachrach ; PMLR 38:489-497

On Estimating L_2^2 Divergence

Akshay Krishnamurthy, Kirthevasan Kandasamy, Barnabas Poczos, Larry Wasserman ; PMLR 38:498-506

Tensor Factorization via Matrix Factorization

Volodymyr Kuleshov, Arun Chaganty, Percy Liang ; PMLR 38:507-516

Low-Rank Spectral Learning with Weighted Loss Functions

Alex Kulesza, Nan Jiang, Satinder Singh ; PMLR 38:517-525

Symmetric Iterative Proportional Fitting

Sven Kurras ; PMLR 38:526-534

Tight Regret Bounds for Stochastic Combinatorial Semi-Bandits

Branislav Kveton, Zheng Wen, Azin Ashkan, Csaba Szepesvari ; PMLR 38:535-543

Sequential Kernel Herding: Frank-Wolfe Optimization for Particle Filtering

Simon Lacoste-Julien, Fredrik Lindsten, Francis Bach ; PMLR 38:544-552

Particle Gibbs for Bayesian Additive Regression Trees

Balaji Lakshminarayanan, Daniel Roy, Yee Whye Teh ; PMLR 38:553-561

Deeply-Supervised Nets

Chen-Yu Lee, Saining Xie, Patrick Gallagher, Zhengyou Zhang, Zhuowen Tu ; PMLR 38:562-570

Preferential Attachment in Graphs with Affinities

Jay Lee, Manzil Zaheer, Stephan Günnemann, Alex Smola ; PMLR 38:571-580

Bayesian Hierarchical Clustering with Exponential Family: Small-Variance Asymptotics and Reducibility

Juho Lee, Seungjin Choi ; PMLR 38:581-589

Modelling Policies in MDPs in Reproducing Kernel Hilbert Space

Guy Lever, Ronnie Stafford ; PMLR 38:590-598

Scalable Optimization of Randomized Operational Decisions in Adversarial Classification Settings

Bo Li, Yevgeniy Vorobeychik ; PMLR 38:599-607

Toward Minimax Off-policy Value Estimation

Lihong Li, Remi Munos, Csaba Szepesvari ; PMLR 38:608-616

Compressed Sensing with Very Sparse Gaussian Random Projections

Ping Li, Cun-Hui Zhang ; PMLR 38:617-625

Max-Margin Zero-Shot Learning for Multi-class Classification

Xin Li, Yuhong Guo ; PMLR 38:626-634

Conditional Restricted Boltzmann Machines for Multi-label Learning with Incomplete Labels

Xin Li, Feipeng Zhao, Yuhong Guo ; PMLR 38:635-643

Sparsistency of \ell_1-Regularized M-Estimators

Yen-Huan Li, Jonathan Scarlett, Pradeep Ravikumar, Volkan Cevher ; PMLR 38:644-652

Similarity Learning for High-Dimensional Sparse Data

Kuan Liu, Aurélien Bellet, Fei Sha ; PMLR 38:653-662

Tradeoffs for Space, Time, Data and Risk in Unsupervised Learning

Mario Lucic, Mesrob Ohannessian, Amin Karbasi, Andreas Krause ; PMLR 38:663-671

Active Pointillistic Pattern Search

Yifei Ma, Dougal Sutherland, Roman Garnett, Jeff Schneider ; PMLR 38:672-680

The Security of Latent Dirichlet Allocation

Shike Mei, Xiaojin Zhu ; PMLR 38:681-689

A Spectral Algorithm for Inference in Hidden semi-Markov Models

Igor Melnyk, Arindam Banerjee ; PMLR 38:690-698

Efficient Training of Structured SVMs via Soft Constraints

Ofer Meshi, Nathan Srebro, Tamir Hazan ; PMLR 38:699-707

Variance Reduction via Antithetic Markov Chains

James Neufeld, Dale Schuurmans, Michael Bowling ; PMLR 38:708-716

Fast Function to Function Regression

Junier Oliva, William Neiswanger, Barnabas Poczos, Eric Xing, Hy Trac, Shirley Ho, Jeff Schneider ; PMLR 38:717-725

Reactive bandits with attitude

Pedro Ortega, Kee-Eung Kim, Daniel Lee ; PMLR 38:726-734

Feature Selection for Linear SVM with Provable Guarantees

Saurabh Paul, Malik Magdon-Ismail, Petros Drineas ; PMLR 38:735-743

On Theoretical Properties of Sum-Product Networks

Robert Peharz, Sebastian Tschiatschek, Franz Pernkopf, Pedro Domingos ; PMLR 38:744-752

Robust sketching for multiple square-root LASSO problems

Vu Pham, Laurent El Ghaoui ; PMLR 38:753-761

Deep Exponential Families

Rajesh Ranganath, Linpeng Tang, Laurent Charlin, David Blei ; PMLR 38:762-771

On the High Dimensional Power of a Linear-Time Two Sample Test under Mean-shift Alternatives

Sashank Reddi, Aaditya Ramdas, Barnabas Poczos, Aarti Singh, Larry Wasserman ; PMLR 38:772-780

A Scalable Algorithm for Structured Kernel Feature Selection

Shaogang Ren, Shuai Huang, John Onofrey, Xenios Papademetris, Xiaoning Qian ; PMLR 38:781-789

Learning Efficient Anomaly Detectors from K-NN Graphs

Jonathan Root, Jing Qian, Venkatesh Saligrama ; PMLR 38:790-799

Gamma Processes, Stick-Breaking, and Variational Inference

Anirban Roychowdhury, Brian Kulis ; PMLR 38:800-808

Direct Density-Derivative Estimation and Its Application in KL-Divergence Approximation

Hiroaki Sasaki, Yung-Kyun Noh, Masashi Sugiyama ; PMLR 38:809-818

Non-Uniform Stochastic Average Gradient Method for Training Conditional Random Fields

Mark Schmidt, Reza Babanezhad, Mohamed Ahmed, Aaron Defazio, Ann Clifton, Anoop Sarkar ; PMLR 38:819-828

Sensor Selection for Crowdsensing Dynamical Systems

Francois Schnitzler, Jia Yuan Yu, Shie Mannor ; PMLR 38:829-837

A Rate of Convergence for Mixture Proportion Estimation, with Application to Learning from Noisy Labels

Clayton Scott ; PMLR 38:838-846

Inference of Cause and Effect with Unsupervised Inverse Regression

Eleni Sgouritsa, Dominik Janzing, Philipp Hennig, Bernhard Schölkopf ; PMLR 38:847-855

Estimation from Pairwise Comparisons: Sharp Minimax Bounds with Topology Dependence

Nihar Shah, Sivaraman Balakrishnan, Joseph Bradley, Abhay Parekh, Kannan Ramchandran, Martin Wainwright ; PMLR 38:856-865

Exploiting Symmetries to Construct Efficient MCMC Algorithms With an Application to SLAM

Roshan Shariff, András György, Csaba Szepesvari ; PMLR 38:866-874

Learning Where to Sample in Structured Prediction

Tianlin Shi, Jacob Steinhardt, Percy Liang ; PMLR 38:875-884

State Space Methods for Efficient Inference in Student-t Process Regression

Arno Solin, Simo Särkkä ; PMLR 38:885-893

Learning from Data with Heterogeneous Noise using SGD

Shuang Song, Kamalika Chaudhuri, Anand Sarwate ; PMLR 38:894-902

Data modeling with the elliptical gamma distribution

Suvrit Sra, Reshad Hosseini, Lucas Theis, Matthias Bethge ; PMLR 38:903-911

WASP: Scalable Bayes via barycenters of subset posteriors

Sanvesh Srivastava, Volkan Cevher, Quoc Dinh, David Dunson ; PMLR 38:912-920

Calibration of conditional composite likelihood for Bayesian inference on Gibbs random fields

Julien Stoehr, Nial Friel ; PMLR 38:921-929

A Dirichlet Process Mixture Model for Spherical Data

Julian Straub, Jason Chang, Oren Freifeld, John Fisher III ; PMLR 38:930-938

Inferring Block Structure of Graphical Models in Exponential Families

Siqi Sun, Hai Wang, Jinbo Xu ; PMLR 38:939-947

Two-stage sampled learning theory on distributions

Zoltan Szabo, Arthur Gretton, Barnabas Poczos, Bharath Sriperumbudur ; PMLR 38:948-957

Predicting Preference Reversals via Gaussian Process Uncertainty Aversion

Rikiya Takahashi, Tetsuro Morimura ; PMLR 38:958-967

Streaming Variational Inference for Bayesian Nonparametric Mixture Models

Alex Tank, Nicholas Foti, Emily Fox ; PMLR 38:968-976

Missing at Random in Graphical Models

Jin Tian ; PMLR 38:977-985

Particle Gibbs with Ancestor Sampling for Probabilistic Programs

Jan-Willem Meent, Hongseok Yang, Vikash Mansinghka, Frank Wood ; PMLR 38:986-994

Learning of Non-Parametric Control Policies with High-Dimensional State Features

Herke Van Hoof, Jan Peters, Gerhard Neumann ; PMLR 38:995-1003

Maximally Informative Hierarchical Representations of High-Dimensional Data

Greg Ver Steeg, Aram Galstyan ; PMLR 38:1004-1012

Falling Rule Lists

Fulton Wang, Cynthia Rudin ; PMLR 38:1013-1022

Multi-Manifold Modeling in Non-Euclidean spaces

Xu Wang, Konstantinos Slavakis, Gilad Lerman ; PMLR 38:1023-1032

Column Subset Selection with Missing Data via Active Sampling

Yining Wang, Aarti Singh ; PMLR 38:1033-1041

Trend Filtering on Graphs

Yu-Xiang Wang, James Sharpnack, Alex Smola, Ryan Tibshirani ; PMLR 38:1042-1050

A Greedy Homotopy Method for Regression with Nonconvex Constraints

Fabian Wauthier, Peter Donnelly ; PMLR 38:1051-1060

Revisiting the Limits of MAP Inference by MWSS on Perfect Graphs

Adrian Weller ; PMLR 38:1061-1069

Understanding and Evaluating Sparse Linear Discriminant Analysis

Yi Wu, David Wipf, Jeong-Min Yun ; PMLR 38:1070-1078

Stochastic Block Transition Models for Dynamic Networks

Kevin Xu ; PMLR 38:1079-1087

Majorization-Minimization for Manifold Embedding

Zhirong Yang, Jaakko Peltonen, Samuel Kaski ; PMLR 38:1088-1097

A la Carte – Learning Fast Kernels

Zichao Yang, Andrew Wilson, Alex Smola, Le Song ; PMLR 38:1098-1106

Minimizing Nonconvex Non-Separable Functions

Yaoliang Yu, Xun Zheng, Micol Marchetti-Bowick, Eric Xing ; PMLR 38:1107-1115

A Simple Homotopy Algorithm for Compressive Sensing

Lijun Zhang, Tianbao Yang, Rong Jin, Zhi-Hua Zhou ; PMLR 38:1116-1124

Scalable Nonparametric Multiway Data Analysis

Shandian Zhe, Zenglin Xu, Xinqi Chu, Yuan Qi, Youngja Park ; PMLR 38:1125-1134

Infinite Edge Partition Models for Overlapping Community Detection and Link Prediction

Mingyuan Zhou ; PMLR 38:1135-1143

Power-Law Graph Cuts

Xiangyang Zhou, Jiaxin Zhang, Brian Kulis ; PMLR 38:1144-1152

The Log-Shift Penalty for Adaptive Estimation of Multiple Gaussian Graphical Models

Yuancheng Zhu, Rina Foygel Barber ; PMLR 38:1153-1161

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