Volume 22: Artificial Intelligence and Statistics, 21-23 April 2012, La Palma, Canary Islands


Editors: Neil D. Lawrence, Mark Girolami





Neil D. Lawrence, Mark Girolami; PMLR 22:i-v

Accepted Papers

Online-to-Confidence-Set Conversions and Application to Sparse Stochastic Bandits

Yasin Abbasi-Yadkori, David Pal, Csaba Szepesvari; PMLR 22:1-9

Discriminative Mixtures of Sparse Latent Fields for Risk Management

Felix Agakov, Peter Orchard, Amos Storkey; PMLR 22:10-18

Contextual Bandit Learning with Predictable Rewards

Alekh Agarwal, Miroslav Dudik, Satyen Kale, John Langford, Robert Schapire; PMLR 22:19-26

Sparse Higher-Order Principal Components Analysis

Genevera Allen; PMLR 22:27-36

Factorized Diffusion Map Approximation

Saeed Amizadeh, Hamed Valizadegan, Milos Hauskrecht; PMLR 22:37-46

Memory-efficient inference in dynamic graphical models using multiple cores

Galen Andrew, Jeff Bilmes; PMLR 22:47-53

Graphlet decomposition of a weighted network

Hossein Azari Soufiani, Edo Airoldi; PMLR 22:54-63

Minimax rates for homology inference

Sivaraman Balakrishnan, Alesandro Rinaldo, Don Sheehy, Aarti Singh, Larry Wasserman; PMLR 22:64-72

Scalable Personalization of Long-Term Physiological Monitoring: Active Learning Methodologies for Epileptic Seizure Onset Detection

Guha Balakrishnan, Zeeshan Syed; PMLR 22:73-81

A General Framework for Structured Sparsity via Proximal Optimization

Luca Baldassarre, Jean Morales, Andreas Argyriou, Massimiliano Pontil; PMLR 22:82-90

Adaptive Metropolis with Online Relabeling

Remi Bardenet, Olivier Cappe, Gersende Fort, Balazs Kegl; PMLR 22:91-99

Controlling Selection Bias in Causal Inference

Elias Bareinboim, Judea Pearl; PMLR 22:100-108

CorrLog: Correlated Logistic Models for Joint Prediction of Multiple Labels

Wei Bian, Bo Xie, Dacheng Tao; PMLR 22:109-117

History-alignment models for bias-aware prediction of virological response to HIV combination therapy

Jasmina Bogojeska, Daniel Stockel, Maurizio Zazzi, Rolf Kaiser, Francesca Incardona, Michal Rosen-Zvi, Thomas Lengauer; PMLR 22:118-126

Joint Learning of Words and Meaning Representations for Open-Text Semantic Parsing

Antoine Bordes, Xavier Glorot, Jason Weston, Yoshua Bengio; PMLR 22:127-135

Sample Complexity of Composite Likelihood

Joseph Bradley, Carlos Guestrin; PMLR 22:136-160

A Family of MCMC Methods on Implicitly Defined Manifolds

Marcus Brubaker, Mathieu Salzmann, Raquel Urtasun; PMLR 22:161-172

On Sparse, Spectral and Other Parameterizations of Binary Probabilistic Models

David Buchman, Mark Schmidt, Shakir Mohamed, David Poole, Nando De Freitas; PMLR 22:173-181

Optimistic planning for Markov decision processes

Lucian Busoniu, Remi Munos; PMLR 22:182-189

Bandit Theory meets Compressed Sensing for high dimensional Stochastic Linear Bandit

Alexandra Carpentier, Remi Munos; PMLR 22:190-198

Structured Sparse Canonical Correlation Analysis

Xi Chen, Liu Han, Jaime Carbonell; PMLR 22:199-207

A Two-Graph Guided Multi-task Lasso Approach for eQTL Mapping

Xiaohui Chen, Xinghua Shi, Xing Xu, Zhiyong Wang, Ryan Mills, Charles Lee, Jinbo Xu; PMLR 22:208-217

Classifier Cascade for Minimizing Feature Evaluation Cost

Minmin Chen, Zhixiang Xu, Kilian Weinberger, Olivier Chapelle, Dor Kedem; PMLR 22:218-226

Online Clustering with Experts

Anna Choromanska, Claire Monteleoni; PMLR 22:227-235

Minimax hypothesis testing for curve registration

Olivier Collier; PMLR 22:236-245

Fast, Exact Model Selection and Permutation Testing for l2-Regularized Logistic Regression

Bryan Conroy, Paul Sajda; PMLR 22:246-254

Gaussian Processes for time-marked time-series data

John Cunningham, Zoubin Ghahramani, Carl Rasmussen; PMLR 22:255-263

Wilks’ phenomenon and penalized likelihood-ratio test for nonparametric curve registration

Arnak Dalalyan, Olivier Collier; PMLR 22:264-272

Hierarchical Relative Entropy Policy Search

Christian Daniel, Gerhard Neumann, Jan Peters; PMLR 22:273-281

Protocols for Learning Classifiers on Distributed Data

Hal Daume III, Jeff Phillips, Avishek Saha, Suresh Venkatasubramanian; PMLR 22:282-290

There’s a Hole in My Data Space: Piecewise Predictors for Heterogeneous Learning Problems

Ofer Dekel, Ohad Shamir; PMLR 22:291-298

Deterministic Annealing for Semi-Supervised Structured Output Learning

Paramveer Dhillon, Sathiya Keerthi, Kedar Bellare, Olivier Chapelle, Sundararajan Sellamanickam; PMLR 22:299-307

A metric learning perspective of SVM: on the relation of LMNN and SVM

Huyen Do, Alexandros Kalousis, Jun Wang, Adam Woznica; PMLR 22:308-317

Generic Methods for Optimization-Based Modeling

Justin Domke; PMLR 22:318-326

Lifted coordinate descent for learning with trace-norm regularization

Miroslav Dudik, Zaid Harchaoui, Jerome Malick; PMLR 22:327-336

Error bounds for Kernel Fisher Linear Discriminant in Gaussian Hilbert space

Robert Durrant, Ata Kaban; PMLR 22:337-345

Copula Network Classifiers (CNCs)

Gal Elidan; PMLR 22:346-354

Lightning-speed Structure Learning of Nonlinear Continuous Networks

Gal Elidan; PMLR 22:355-363

Statistical test for consistent estimation of causal effects in linear non-Gaussian models

Doris Entner, Patrik Hoyer, Peter Spirtes; PMLR 22:364-372

High-Rank Matrix Completion

Brian Eriksson, Laura Balzano, Robert Nowak; PMLR 22:373-381

No Internal Regret via Neighborhood Watch

Dean Foster, Alexander Rakhlin; PMLR 22:382-390

Semiparametric Pseudo-Likelihood Estimation in Markov Random Fields

Antonino Freno; PMLR 22:391-399

Factorized Asymptotic Bayesian Inference for Mixture Modeling

Ryohei Fujimaki, Satoshi Morinaga; PMLR 22:400-408

Hierarchical Latent Dictionaries for Models of Brain Activation

Alona Fyshe, Emily Fox, David Dunson, Tom Mitchell; PMLR 22:409-421

UPAL: Unbiased Pool Based Active Learning

Ravi Ganti, Alexander Gray; PMLR 22:422-431

Regularization Paths with Guarantees for Convex Semidefinite Optimization

Joachim Giesen, Martin Jaggi, Soeren Laue; PMLR 22:432-439

Scalable Inference on Kingman’s Coalescent using Pair Similarity

Dilan Gorur, Levi Boyles, Max Welling; PMLR 22:440-448

On Average Reward Policy Evaluation in Infinite-State Partially Observable Systems

Yuri Grinberg, Doina Precup; PMLR 22:449-457

SpeedBoost: Anytime Prediction with Uniform Near-Optimality

Alex Grubb, Drew Bagnell; PMLR 22:458-466

Bayesian regularization of non-homogeneous dynamic Bayesian networks by globally coupling interaction parameters

Marco Grzegorzyk, Dirk Husmeier; PMLR 22:467-476

Locality Preserving Feature Learning

Quanquan Gu, Marina Danilevsky, Zhenhui Li, Jiawei Han; PMLR 22:477-485

Evaluation of marginal likelihoods via the density of states

Michael Habeck; PMLR 22:486-494

Information Theoretic Model Validation for Spectral Clustering

Morteza Haghir Chehreghani, Alberto Giovanni Busetto, Joachim M. Buhmann; PMLR 22:495-503

Exchangeability Characterizes Optimality of Sequential Normalized Maximum Likelihood and Bayesian Prediction with Jeffreys Prior

Fares Hedayati, Peter Bartlett; PMLR 22:504-510

Kernel Topic Models

Philipp Hennig, David Stern, Ralf Herbrich, Thore Graepel; PMLR 22:511-519

Maximum Margin Temporal Clustering

Minh Hoai, Fernando De La Torre; PMLR 22:520-528

Stochastic Bandit Based on Empirical Moments

Junya Honda, Akimichi Takemura; PMLR 22:529-537

Variable Selection for Gaussian Graphical Models

Jean Honorio, Dimitris Samaras, Irina Rish, Guillermo Cecchi; PMLR 22:538-546

Subset Infinite Relational Models

Katsuhiko Ishiguro, Naonori Ueda, Hiroshi Sawada; PMLR 22:547-555

A Variance Minimization Criterion to Active Learning on Graphs

Ming Ji, Jiawei Han; PMLR 22:556-564

Detecting Network Cliques with Radon Basis Pursuit

Xiaoye Jiang, Yuan Yao, Han Liu, Leonidas Guibas; PMLR 22:565-573

High-dimensional Sparse Inverse Covariance Estimation using Greedy Methods

Christopher Johnson, Ali Jalali, Pradeep Ravikumar; PMLR 22:574-582

Random Feature Maps for Dot Product Kernels

Purushottam Kar, Harish Karnick; PMLR 22:583-591

On Bayesian Upper Confidence Bounds for Bandit Problems

Emilie Kaufmann, Olivier Cappe, Aurelien Garivier; PMLR 22:592-600

Online Clustering of Processes

Azadeh Khaleghi, Daniil Ryabko, Jeremie Mary, Philippe Preux; PMLR 22:601-609

A Stick-Breaking Likelihood for Categorical Data Analysis with Latent Gaussian Models

Mohammad Khan, Shakir Mohamed, Benjamin Marlin, Kevin Murphy; PMLR 22:610-618

Bayesian Classifier Combination

Hyun-Chul Kim, Zoubin Ghahramani; PMLR 22:619-627

Regression for sets of polynomial equations

Franz Kiraly, Paul Von Buenau, Jan Muller, Duncan Blythe, Frank Meinecke, Klaus-Robert Muller; PMLR 22:628-637

Multiple Texture Boltzmann Machines

Jyri Kivinen, Christopher Williams; PMLR 22:638-646

Marginal Regression For Multitask Learning

Mladen Kolar, Han Liu; PMLR 22:647-655

Message-Passing Algorithms for MAP Estimation Using DC Programming

Akshat Kumar, Shlomo Zilberstein, Marc Toussaint; PMLR 22:656-664

Bayesian Comparison of Machine Learning Algorithms on Single and Multiple Datasets

Alexandre Lacoste, Francois Laviolette, Mario Marchand; PMLR 22:665-675

Efficient Hypergraph Clustering

Marius Leordeanu, Cristian Sminchisescu; PMLR 22:676-684

Data dependent kernels in nearly-linear time

Guy Lever, Tom Diethe, John Shawe-Taylor; PMLR 22:685-693

Efficient Sampling from Combinatorial Space via Bridging

Dahua Lin, John Fisher; PMLR 22:694-702

Exact Subspace Segmentation and Outlier Detection by Low-Rank Representation

Guangcan Liu, Huan Xu, Shuicheng Yan; PMLR 22:703-711

High-Dimensional Structured Feature Screening Using Binary Markov Random Fields

Jie Liu, Chunming Zhang, Catherine Mccarty, Peggy Peissig, Elizabeth Burnside, David Page; PMLR 22:712-721

A Simple Geometric Interpretation of SVM using Stochastic Adversaries

Roi Livni, Koby Crammer, Amir Globerson; PMLR 22:722-730

Closed-Form Entropy Limits - A Tool to Monitor Likelihood Optimization of Probabilistic Generative Models

Jorg Lucke, Marc Henniges; PMLR 22:731-740

Efficient Gaussian Process Inference for Short-Scale Spatio-Temporal Modeling

Jaakko Luttinen, Alexander Ilin; PMLR 22:741-750

Adaptive MCMC with Bayesian Optimization

Nimalan Mahendran, Ziyu Wang, Firas Hamze, Nando De Freitas; PMLR 22:751-760

Movement Segmentation and Recognition for Imitation Learning

Franziska Meier, Evangelos Theodorou, Stefan Schaal; PMLR 22:761-769

Globally Optimizing Graph Partitioning Problems Using Message Passing

Elad Mezuman, Yair Weiss; PMLR 22:770-778

Max-Margin Min-Entropy Models

Kevin Miller, M. Pawan Kumar, Ben Packer, Danny Goodman, Daphne Koller; PMLR 22:779-787

Lifted Linear Programming

Martin Mladenov, Babak Ahmadi, Kristian Kersting; PMLR 22:788-797

Deep Boltzmann Machines as Feed-Forward Hierarchies

Gregoire Montavon, Mikio Braun, Klaus-Robert Muller; PMLR 22:798-804

The adversarial stochastic shortest path problem with unknown transition probabilities

Gergely Neu, Andras Gyorgy, Csaba Szepesvari; PMLR 22:805-813

A Nonparametric Bayesian Model for Multiple Clustering with Overlapping Feature Views

Donglin Niu, Jennifer Dy, Zoubin Ghahramani; PMLR 22:814-822

Beyond Logarithmic Bounds in Online Learning

Francesco Orabona, Nicolo Cesa-Bianchi, Claudio Gentile; PMLR 22:823-831

Bayesian Quadrature for Ratios

Michael Osborne, Roman Garnett, Stephen Roberts, Christopher Hart, Suzanne Aigrain, Neale Gibson; PMLR 22:832-840

Probabilistic acoustic tube: a probabilistic generative model of speech for speech analysis/synthesis

Zhijian Ou, Yang Zhang; PMLR 22:841-849

Stick-Breaking Beta Processes and the Poisson Process

John Paisley, David Blei, Michael Jordan; PMLR 22:850-858

On a Connection between Maximum Variance Unfolding, Shortest Path Problems and IsoMap

Alexander Paprotny, Jochen Garcke; PMLR 22:859-867

Approximate Inference by Intersecting Semidefinite Bound and Local Polytope

Jian Peng, Tamir Hazan, Nathan Srebro, Jinbo Xu; PMLR 22:868-876

Part & Clamp: Efficient Structured Output Learning

Patrick Pletscher, Cheng Soon Ong; PMLR 22:877-885

Learning Low-order Models for Enforcing High-order Statistics

Patrick Pletscher, Pushmeet Kohli; PMLR 22:886-894

Fast interior-point inference in high-dimensional sparse, penalized state-space models

Eftychios Pnevmatikakis, Liam Paninski; PMLR 22:895-904

Informative Priors for Markov Blanket Discovery

Adam Pocock, Mikel Lujan, Gavin Brown; PMLR 22:905-913

Nonparametric Estimation of Conditional Information and Divergences

Barnabas Poczos, Jeff Schneider; PMLR 22:914-923

Deep Learning Made Easier by Linear Transformations in Perceptrons

Tapani Raiko, Harri Valpola, Yann Lecun; PMLR 22:924-932

A Differentially Private Stochastic Gradient Descent Algorithm for Multiparty Classification

Arun Rajkumar, Shivani Agarwal; PMLR 22:933-941

Universal Measurement Bounds for Structured Sparse Signal Recovery

Nikhil Rao, Ben Recht, Robert Nowak; PMLR 22:942-950

Exploiting Unrelated Tasks in Multi-Task Learning

Bernardino Romera Paredes, Andreas Argyriou, Nadia Berthouze, Massimiliano Pontil; PMLR 22:951-959

Domain Adaptation: A Small Sample Statistical Approach

Ruslan Salakhutdinov, Sham Kakade, Dean Foster; PMLR 22:960-968

Local Anomaly Detection

Venkatesh Saligrama, Manqi Zhao; PMLR 22:969-983

Age-Layered Expectation Maximization for Parameter Learning in Bayesian Networks

Avneesh Saluja, Priya Krishnan Sundararajan, Ole J Mengshoel; PMLR 22:984-992

Infinite-Dimensional Kalman Filtering Approach to Spatio-Temporal Gaussian Process Regression

Simo Sarkka, Jouni Hartikainen; PMLR 22:993-1001

Markov Logic Mixtures of Gaussian Processes: Towards Machines Reading Regression Data

Martin Schiegg, Marion Neumann, Kristian Kersting; PMLR 22:1002-1011

Fast Variational Bayesian Inference for Non-Conjugate Matrix Factorization Models

Matthias Seeger, Guillaume Bouchard; PMLR 22:1012-1018

Using More Data to Speed-up Training Time

Shai Shalev-Shwartz, Ohad Shamir, Eran Tromer; PMLR 22:1019-1027

Sparsistency of the Edge Lasso over Graphs

James Sharpnack, Aarti Singh, Alessandro Rinaldo; PMLR 22:1028-1036

Complexity of Bethe Approximation

Jinwoo Shin; PMLR 22:1037-1045

Multi-armed Bandit Problems with History

Pannagadatta Shivaswamy, Thorsten Joachims; PMLR 22:1046-1054

On Bisubmodular Maximization

Ajit Singh, Andrew Guillory, Jeff Bilmes; PMLR 22:1055-1063

Low rank continuous-space graphical models

Carl Smith, Frank Wood, Liam Paninski; PMLR 22:1064-1072

On Nonparametric Guidance for Learning Autoencoder Representations

Jasper Snoek, Ryan Adams, Hugo Larochelle; PMLR 22:1073-1080

Joint Estimation of Structured Sparsity and Output Structure in Multiple-Output Regression via Inverse-Covariance Regularization

Kyung-Ah Sohn, Seyoung Kim; PMLR 22:1081-1089

Consistency and Rates for Clustering with DBSCAN

Bharath Sriperumbudur, Ingo Steinwart; PMLR 22:1090-1098

Testing for Membership to the IFRA and the NBU Classes of Distributions

Radhendushka Srivastava, Ping Li, Debasis Sengupta; PMLR 22:1099-1107

Flexible Martingale Priors for Deep Hierarchies

Jacob Steinhardt, Zoubin Ghahramani; PMLR 22:1108-1116

Bayesian Inference for Change Points in Dynamical Systems with Reusable States - a Chinese Restaurant Process Approach

Florian Stimberg, Andreas Ruttor, Manfred Opper; PMLR 22:1117-1124

Learning Fourier Sparse Set Functions

Peter Stobbe, Andreas Krause; PMLR 22:1125-1133

Efficient and Exact MAP-MRF Inference using Branch and Bound

Min Sun, Murali Telaprolu, Honglak Lee, Silvio Savarese; PMLR 22:1134-1142

Constrained 1-Spectral Clustering

Syama Sundar Rangapuram, Matthias Hein; PMLR 22:1143-1151

Fast Learning Rate of Multiple Kernel Learning: Trade-Off between Sparsity and Smoothness

Taiji Suzuki, Masashi Sugiyama; PMLR 22:1152-1183

On Estimation and Selection for Topic Models

Matt Taddy; PMLR 22:1184-1193

Lifted Variable Elimination with Arbitrary Constraints

Nima Taghipour, Daan Fierens, Jesse Davis, Hendrik Blockeel; PMLR 22:1194-1202

Multiresolution Deep Belief Networks

Yichuan Tang, Abdel-Rahman Mohamed; PMLR 22:1203-1211

Structured Output Learning with High Order Loss Functions

Daniel Tarlow, Richard Zemel; PMLR 22:1212-1220

Randomized Optimum Models for Structured Prediction

Daniel Tarlow, Ryan Adams, Richard Zemel; PMLR 22:1221-1229

Fast Variational Mode-Seeking

Bo Thiesson, Jingu Kim; PMLR 22:1230-1242

A Bayesian Analysis of the Radioactive Releases of Fukushima

Ryota Tomioka, Morten Mrup; PMLR 22:1243-1251

Learning from Weak Teachers

Ruth Urner, Shai Ben David, Ohad Shamir; PMLR 22:1252-1260

Krylov Subspace Descent for Deep Learning

Oriol Vinyals, Daniel Povey; PMLR 22:1261-1268

Bayesian Group Factor Analysis

Seppo Virtanen, Arto Klami, Suleiman Khan, Samuel Kaski; PMLR 22:1269-1277

Minimax Rates of Estimation for Sparse PCA in High Dimensions

Vincent Vu, Jing Lei; PMLR 22:1278-1286

A Hybrid Neural Network-Latent Topic Model

Li Wan, Leo Zhu, Rob Fergus; PMLR 22:1287-1294

Nonlinear low-dimensional regression using auxiliary coordinates

Weiran Wang, Miguel Carreira-Perpinan; PMLR 22:1295-1304

Generalized Optimal Reverse Prediction

Martha White, Dale Schuurmans; PMLR 22:1305-1313

Causality with Gates

John Winn; PMLR 22:1314-1322

Primal-Dual methods for sparse constrained matrix completion

Yu Xin, Tommi Jaakkola; PMLR 22:1323-1331

Statistical Optimization in High Dimensions

Huan Xu, Constantine Caramanis, Shie Mannor; PMLR 22:1332-1340

Robust Multi-task Regression with Grossly Corrupted Observations

Huan Xu, Chenlei Leng; PMLR 22:1341-1349

Active Learning from Multiple Knowledge Sources

Yan Yan, Romer Rosales, Glenn Fung, Faisal Farooq, Bharat Rao, Jennifer Dy; PMLR 22:1350-1357

Perturbation based Large Margin Approach for Ranking

Eunho Yang, Ambuj Tewari, Pradeep Ravikumar; PMLR 22:1358-1366

Transductive Learning of Structural SVMs via Prior Knowledge Constraints

Chun-Nam Yu; PMLR 22:1367-1376

Forward Basis Selection for Sparse Approximation over Dictionary

Xiaotong Yuan, Shuicheng Yan; PMLR 22:1377-1388

Quilting Stochastic Kronecker Product Graphs to Generate Multiplicative Attribute Graphs

Hyokun Yun, S V N Vishwanathan; PMLR 22:1389-1397

Efficient Distributed Linear Classification Algorithms via the Alternating Direction Method of Multipliers

Caoxie Zhang, Honglak Lee, Kang Shin; PMLR 22:1398-1406

A Composite Likelihood View for Multi-Label Classification

Yi Zhang, Jeff Schneider; PMLR 22:1407-1415

An Autoregressive Approach to Nonparametric Hierarchical Dependent Modeling

Zhihua Zhang, Dakan Wang, Edward Chang; PMLR 22:1416-1424

Scaling up Kernel SVM on Limited Resources: A Low-rank Linearization Approach

Kai Zhang, Liang Lan, Zhuang Wang, Fabian Moerchen; PMLR 22:1425-1434

Sparse Additive Machine

Tuo Zhao, Han Liu; PMLR 22:1435-1443

Multi-label Subspace Ensemble

Tianyi Zhou, Dacheng Tao; PMLR 22:1444-1452

Online Incremental Feature Learning with Denoising Autoencoders

Guanyu Zhou, Kihyuk Sohn, Honglak Lee; PMLR 22:1453-1461

Beta-Negative Binomial Process and Poisson Factor Analysis

Mingyuan Zhou, Lauren Hannah, David Dunson, Lawrence Carin; PMLR 22:1462-1471

Approximate Inference in Additive Factorial HMMs with Application to Energy Disaggregation

J. Zico Kolter, Tommi Jaakkola; PMLR 22:1472-1482

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