Volume 15: Proceedings of the Fourteenth International Conference on Artificial Intelligence and Statistics, 11-13 April 2011, Fort Lauderdale, FL, USA


Editors: Geoffrey Gordon, David Dunson, Miroslav Dudík





Geoffrey Gordon, David Dunson ; PMLR 15:1-2

Part I: Notable Papers

Learning equivalence classes of acyclic models with latent and selection variables from multiple datasets with overlapping variables

Robert Tillman, Peter Spirtes ; PMLR 15:3-15

Discussion of “Learning Equivalence Classes of Acyclic Models with Latent and Selection Variables from Multiple Datasets with Overlapping Variables”

Jiji Zhang, Ricardo Silva ; PMLR 15:16-18

Contextual Bandit Algorithms with Supervised Learning Guarantees

Alina Beygelzimer, John Langford, Lihong Li, Lev Reyzin, Robert Schapire ; PMLR 15:19-26

Discussion of “Contextual Bandit Algorithms with Supervised Learning Guarantees”

Brendan McMahan ; PMLR 15:27-28

The Neural Autoregressive Distribution Estimator

Hugo Larochelle, Iain Murray ; PMLR 15:29-37

Discussion of “The Neural Autoregressive Distribution Estimator”

Yoshua Bengio ; PMLR 15:38-39

Learning Scale Free Networks by Reweighted L1 regularization

Qiang Liu, Alexander Ihler ; PMLR 15:40-48

Discussion of “Learning Scale Free Networks by Reweighted L1 regularization”

Deepak Agarwal ; PMLR 15:49-50

Spectral Dimensionality Reduction via Maximum Entropy

Neil Lawrence ; PMLR 15:51-59

Discussion of “Spectral Dimensionality Reduction via Maximum Entropy”

Laurens van der Maaten ; PMLR 15:60-62

A conditional game for comparing approximations

Frederik Eaton ; PMLR 15:63-71

Discussion of “A conditional game for comparing approximations”

Vincent Conitzer ; PMLR 15:72-73

The Discrete Infinite Logistic Normal Distribution for Mixed-Membership Modeling

John Paisley, Chong Wang, David Blei ; PMLR 15:74-82

Discussion of “The Discrete Infinite Logistic Normal Distribution for Mixed-Membership Modeling”

Frank Wood ; PMLR 15:83-84

Part II: Regular Papers

Generative Kernels for Exponential Families

Arvind Agarwal, Hal Daumé III ; PMLR 15:85-92

Linear-Time Estimators for Propensity Scores

Deepak Agarwal, Lihong Li, Alexander Smola ; PMLR 15:93-100

Online Inference for the Infinite Topic-Cluster Model: Storylines from Streaming Text

Amr Ahmed, Qirong Ho, Choon Hui Teo, Jacob Eisenstein, Alex Smola, Eric Xing ; PMLR 15:101-109

Polytope samplers for inference in ill-posed inverse problems

Edoardo Airoldi, Bertrand Haas ; PMLR 15:110-118

Dynamic Policy Programming with Function Approximation

Mohammad Gheshlaghi Azar, Vicenç Gómez, Bert Kappen ; PMLR 15:119-127

Statistical Optimization of Non-Negative Matrix Factorization

Anoop Korattikara Balan, Levi Boyles, Max Welling, Jingu Kim, Haesun Park ; PMLR 15:128-136

Unsupervised Supervised Learning II: Margin-Based Classification without Labels

Krishnakumar Balasubramanian, Pinar Donmez, Guy Lebanon ; PMLR 15:137-145

Tighter Relaxations for MAP-MRF Inference: A Local Primal-Dual Gap based Separation Algorithm

Dhruv Batra, Sebastian Nowozin, Pushmeet Kohli ; PMLR 15:146-154

Active Diagnosis under Persistent Noise with Unknown Noise Distribution: A Rank-Based Approach

Gowtham Bellala, Suresh Bhavnani, Clayton Scott ; PMLR 15:155-163

Deep Learners Benefit More from Out-of-Distribution Examples

Yoshua Bengio, Frédéric Bastien, Arnaud Bergeron, Nicolas Boulanger–Lewandowski, Thomas Breuel, Youssouf Chherawala, Moustapha Cisse, Myriam Côté, Dumitru Erhan, Jeremy Eustache, Xavier Glorot, Xavier Muller, Sylvain Pannetier Lebeuf, Razvan Pascanu, Salah Rifai, François Savard, Guillaume Sicard ; PMLR 15:164-172

Domain Adaptation with Coupled Subspaces

John Blitzer, Sham Kakade, Dean Foster ; PMLR 15:173-181

Relative Entropy Inverse Reinforcement Learning

Abdeslam Boularias, Jens Kober, Jan Peters ; PMLR 15:182-189

Switch-Reset Models : Exact and Approximate Inference

Chris Bracegirdle, David Barber ; PMLR 15:190-198

Concave Gaussian Variational Approximations for Inference in Large-Scale Bayesian Linear Models

Edward Challis, David Barber ; PMLR 15:199-207

Contextual Bandits with Linear Payoff Functions

Wei Chu, Lihong Li, Lev Reyzin, Robert Schapire ; PMLR 15:208-214

An Analysis of Single-Layer Networks in Unsupervised Feature Learning

Adam Coates, Andrew Ng, Honglak Lee ; PMLR 15:215-223

Deep Learning for Efficient Discriminative Parsing

Ronan Collobert ; PMLR 15:224-232

A Spike and Slab Restricted Boltzmann Machine

Aaron Courville, James Bergstra, Yoshua Bengio ; PMLR 15:233-241

Optimal and Robust Price Experimentation: Learning by Lottery

Christopher Dance, Onno Zoeter ; PMLR 15:242-250

Bagged Structure Learning of Bayesian Network

Gal Elidan ; PMLR 15:251-259

Active Clustering: Robust and Efficient Hierarchical Clustering using Adaptively Selected Similarities

Brian Eriksson, Gautam Dasarathy, Aarti Singh, Rob Nowak ; PMLR 15:260-268

A novel greedy algorithm for Nyström approximation

Ahmed Farahat, Ali Ghodsi, Mohamed Kamel ; PMLR 15:269-277

Revisiting MAP Estimation, Message Passing and Perfect Graphs

James Foulds, Nicholas Navaroli, Padhraic Smyth, Alexander Ihler ; PMLR 15:278-286

A Dynamic Relational Infinite Feature Model for Longitudinal Social Networks

James Foulds, Christopher DuBois, Arthur Asuncion, Carter Butts, Padhraic Smyth ; PMLR 15:287-295

Block-sparse Solutions using Kernel Block RIP and its Application to Group Lasso

Rahul Garg, Rohit Khandekar ; PMLR 15:296-304

Learning from positive and unlabeled examples by enforcing statistical significance

Pierre Geurts ; PMLR 15:305-314

Deep Sparse Rectifier Neural Networks

Xavier Glorot, Antoine Bordes, Yoshua Bengio ; PMLR 15:315-323

Parallel Gibbs Sampling: From Colored Fields to Thin Junction Trees

Joseph Gonzalez, Yucheng Low, Arthur Gretton, Carlos Guestrin ; PMLR 15:324-332

Multiscale Community Blockmodel for Network Exploration

Qirong Ho, Ankur Parikh, Le Song, Eric Xing ; PMLR 15:333-341

Evolving Cluster Mixed-Membership Blockmodel for Time-Evolving Networks

Qirong Ho, Le Song, Eric Xing ; PMLR 15:342-350

Optimal Distributed Market-Based Planning for Multi-Agent Systems with Shared Resources

Sue Ann Hong, Geoffrey Gordon ; PMLR 15:351-360

Fast b-matching via Sufficient Selection Belief Propagation

Bert Huang, Tony Jebara ; PMLR 15:361-369

Improved Loss Bounds For Multiple Kernel Learning

Zakria Hussain, John Shawe–Taylor ; PMLR 15:370-377

On Learning Discrete Graphical Models using Group-Sparse Regularization

Ali Jalali, Pradeep Ravikumar, Vishvas Vasuki, Sujay Sanghavi ; PMLR 15:378-387

Convergent Decomposition Solvers for Tree-reweighted Free Energies

Jeremy Jancsary, Gerald Matz ; PMLR 15:388-398

Convex envelopes of complexity controlling penalties: the case against premature envelopment

Vladimir Jojic, Suchi Saria, Daphne Koller ; PMLR 15:399-406

On Time Varying Undirected Graphs

Mladen Kolar, Eric Xing ; PMLR 15:407-415

Approximate inference for the loss-calibrated Bayesian

Simon Lacoste–Julien, Ferenc Huszár, Zoubin Ghahramani ; PMLR 15:416-424

Robust Bayesian Matrix Factorisation

Balaji Lakshminarayanan, Guillaume Bouchard, Cedric Archambeau ; PMLR 15:425-433

Confidence Weighted Mean Reversion Strategy for On-Line Portfolio Selection

Bin Li, Steven C.H. Hoi, Peilin Zhao, Vivekanand Gopalkrishnan ; PMLR 15:434-442

Bayesian Hierarchical Cross-Clustering

Dazhuo Li, Patrick Shafto ; PMLR 15:443-451

Group Orthogonal Matching Pursuit for Logistic Regression

Aurelie Lozano, Grzegorz Swirszcz, Naoki Abe ; PMLR 15:452-460

A Fast Algorithm for Recovery of Jointly Sparse Vectors based on the Alternating Direction Methods

Hongtao Lu, Xianzhong Long, Jingyuan Lv ; PMLR 15:461-469

Learning Class-relevant Features and Class-irrelevant Features via a Hybrid third-order RBM

Heng Luo, Ruimin Shen, Changyong Niu, Carsten Ullrich ; PMLR 15:470-478

Hidden-Unit Conditional Random Fields

Laurens van der Maaten, Max Welling, Lawrence Saul ; PMLR 15:479-488

Learning mixtures of Gaussians with maximum-a-posteriori oracle

Satyaki Mahalanabis ; PMLR 15:489-497

CAKE: Convex Adaptive Kernel Density Estimation

Ravi Sastry Ganti Mahapatruni, Alexander Gray ; PMLR 15:498-506

Online Learning of Structured Predictors with Multiple Kernels

Andre Filipe Torres Martins, Noah Smith, Eric Xing, Pedro Aguiar, Mario Figueiredo ; PMLR 15:507-515

Estimating beta-mixing coefficients

Daniel McDonald, Cosma Shalizi, Mark Schervish ; PMLR 15:516-524

Follow-the-Regularized-Leader and Mirror Descent: Equivalence Theorems and L1 Regularization

Brendan McMahan ; PMLR 15:525-533

Can matrix coherence be efficiently and accurately estimated?

Mehryar Mohri, Ameet Talwalkar ; PMLR 15:534-542

TopicFlow Model: Unsupervised Learning of Topic-specific Influences of Hyperlinked Documents

Ramesh Nallapati, Daniel McFarland, Christopher Manning ; PMLR 15:543-551

Dimensionality Reduction for Spectral Clustering

Donglin Niu, Jennifer Dy, Michael I. Jordan ; PMLR 15:552-560

Maximum Volume Clustering

Gang Niu, Bo Dai, Lin Shang, Masashi Sugiyama ; PMLR 15:561-569

Adaptive Bandits: Towards the best history-dependent strategy

Maillard Odalric, Remi Munos ; PMLR 15:570-578

Generative Modeling for Maximizing Precision and Recall in Information Visualization

Jaakko Peltonen, Samuel Kaski ; PMLR 15:579-587

Faithfulness in Chain Graphs: The Gaussian Case

Jose M. Peña ; PMLR 15:588-599

Directional Statistics on Permutations

Sergey Plis, Stephen McCracken, Terran Lane, Vince Calhoun ; PMLR 15:600-608

On the Estimation of alpha-Divergences

Barnabas Poczos, Jeff Schneider ; PMLR 15:609-617

On NDCG Consistency of Listwise Ranking Methods

Pradeep Ravikumar, Ambuj Tewari, Eunho Yang ; PMLR 15:618-626

A Reduction of Imitation Learning and Structured Prediction to No-Regret Online Learning

Stephane Ross, Geoffrey Gordon, Drew Bagnell ; PMLR 15:627-635

Improved Regret Guarantees for Online Smooth Convex Optimization with Bandit Feedback

Ankan Saha, Ambuj Tewari ; PMLR 15:636-642

Online Learning of Multiple Tasks and Their Relationships

Avishek Saha, Piyush Rai, Hal Daumé III, Suresh Venkatasubramanian ; PMLR 15:643-651

Fast Convergent Algorithms for Expectation Propagation Approximate Bayesian Inference

Matthias Seeger, Hannes Nickisch ; PMLR 15:652-660

Spectral Clustering on a Budget

Ohad Shamir, Naftali Tishby ; PMLR 15:661-669

Mixed Cumulative Distribution Networks

Ricardo Silva, Charles Blundell, Yee Whye Teh ; PMLR 15:670-678

Asymptotic Theory for Linear-Chain Conditional Random Fields

Mathieu Sinn, Pascal Poupart ; PMLR 15:679-687

Assisting Main Task Learning by Heterogeneous Auxiliary Tasks with Applications to Skin Cancer Screening

Ning Situ, Xiaojing Yuan, George Zouridakis ; PMLR 15:688-697

Spectral Chinese Restaurant Processes: Nonparametric Clustering Based on Similarities

Richard Socher, Andrew Maas, Christopher Manning ; PMLR 15:698-706

Kernel Belief Propagation

Le Song, Arthur Gretton, Danny Bickson, Yucheng Low, Carlos Guestrin ; PMLR 15:707-715

Machine Learning Markets

Amos Storkey ; PMLR 15:716-724

Empirical Risk Minimization of Graphical Model Parameters Given Approximate Inference, Decoding, and Model Structure

Veselin Stoyanov, Alexander Ropson, Jason Eisner ; PMLR 15:725-733

Estimating Probabilities in Recommendation Systems

Mingxuan Sun, Guy Lebanon, Paul Kidwell ; PMLR 15:734-742

Active Boosted Learning (ActBoost)

Kirill Trapeznikov, Venkatesh Saligrama, David Castanon ; PMLR 15:743-751

Online Variational Inference for the Hierarchical Dirichlet Process

Chong Wang, John Paisley, David Blei ; PMLR 15:752-760

Information Theoretical Clustering via Semidefinite Programming

Meihong Wang, Fei Sha ; PMLR 15:761-769

Lightweight Implementations of Probabilistic Programming Languages Via Transformational Compilation

David Wingate, Andreas Stuhlmueller, Noah Goodman ; PMLR 15:770-778

Relational Learning with One Network: An Asymptotic Analysis

Rongjing Xiang, Jennifer Neville ; PMLR 15:779-788

Hierarchical Probabilistic Models for Group Anomaly Detection

Liang Xiong, Barnabas Poczos, Jeff Schneider, Andrew Connolly, Jake VanderPlas ; PMLR 15:789-797

Multicore Gibbs Sampling in Dense, Unstructured Graphs

Tianbing Xu, Alexander Ihler ; PMLR 15:798-806

Cross-Domain Object Matching with Model Selection

Makoto Yamada, Masashi Sugiyama ; PMLR 15:807-815

The Sample Complexity of Self-Verifying Bayesian Active Learning

Liu Yang, Steve Hanneke, Jaime Carbonell ; PMLR 15:816-822

Bridging the Language Gap: Topic Adaptation for Documents with Different Technicality

Shuang–Hong Yang, Steven Crain, Hongyuan Zha ; PMLR 15:823-831

Efficient variable selection in support vector machines via the alternating direction method of multipliers

Gui–Bo Ye, Yifei Chen, Xiaohui Xie ; PMLR 15:832-840

A Finite Newton Algorithm for Non-degenerate Piecewise Linear Systems

Xiao–Tong Yuan, Shuicheng Yan ; PMLR 15:841-854

An Instantiation-Based Theorem Prover for First-Order Programming

Erik Zawadzki, Geoffrey Gordon, Andre Platzer ; PMLR 15:855-863

Generalization Bound for Infinitely Divisible Empirical Process

Chao Zhang, Dacheng Tao ; PMLR 15:864-872

Multi-Label Output Codes using Canonical Correlation Analysis

Yi Zhang, Jeff Schneider ; PMLR 15:873-882

Dependent Hierarchical Beta Process for Image Interpolation and Denoising

Mingyuan Zhou, Hongxia Yang, Guillermo Sapiro, David Dunson, Lawrence Carin ; PMLR 15:883-891

Semi-supervised Learning by Higher Order Regularization

Xueyuan Zhou, Mikhail Belkin ; PMLR 15:892-900

Error Analysis of Laplacian Eigenmaps for Semi-supervised Learning

Xueyuan Zhou, Nathan Srebro ; PMLR 15:901-908

Two-Layer Multiple Kernel Learning

Jinfeng Zhuang, Ivor W. Tsang, Steven C.H. Hoi ; PMLR 15:909-917

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