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JMLR Workshop and Conference Proceedings

Volume 33: Proceedings of the Seventeenth International Conference on Artificial Intelligence and Statistics

Editors: Samuel Kaski, Jukka Corander

Contents:

Preface

Preface

Samuel Kaski, Jukka Corander ; JMLR W&CP 33 :i-iv, 2014

Notable Papers

Decontamination of Mutually Contaminated Models

Gilles Blanchard, Clayton Scott ; JMLR W&CP 33 :1-9, 2014

Distributed optimization of deeply nested systems

Miguel Carreira-Perpinan, Weiran Wang ; JMLR W&CP 33 :10-19, 2014

Analysis of Empirical MAP and Empirical Partially Bayes: Can They be Alternatives to Variational Bayes?

Shinichi Nakajima, Masashi Sugiyama ; JMLR W&CP 33 :20-28, 2014

Regular Papers

Improved Bounds for Online Learning Over the Permutahedron and Other Ranking Polytopes

Nir Ailon ; JMLR W&CP 33 :29-37, 2014

Information-Theoretic Characterization of Sparse Recovery

Cem Aksoylar, Venkatesh Saligrama ; JMLR W&CP 33 :38-46, 2014

Hybrid Discriminative-Generative Approach with Gaussian Processes

Ricardo Andrade Pacheco, James Hensman, Max Zwiessele, Neil Lawrence ; JMLR W&CP 33 :47-56, 2014

Average Case Analysis of High-Dimensional Block-Sparse Recovery and Regression for Arbitrary Designs

Waheed Bajwa, Marco Duarte, Robert Calderbank ; JMLR W&CP 33 :57-67, 2014

A New Perspective on Learning Linear Separators with Large \(L_qL_p\) Margins

Maria-Florina Balcan, Christopher Berlind ; JMLR W&CP 33 :68-76, 2014

A Non-parametric Conditional Factor Regression Model for Multi-Dimensional Input and Response

Ava Bargi, Richard Yi Xu, Zoubin Ghahramani, Massimo Piccardi ; JMLR W&CP 33 :77-85, 2014

Learning Optimal Bounded Treewidth Bayesian Networks via Maximum Satisfiability

Jeremias Berg, Matti Järvisalo, Brandon Malone ; JMLR W&CP 33 :86-95, 2014

Online Passive-Aggressive Algorithms for Non-Negative Matrix Factorization and Completion

Mathieu Blondel, Yotaro Kubo, Ueda Naonori ; JMLR W&CP 33 :96-104, 2014

PAC-Bayesian Theory for Transductive Learning

Luc Bégin, Pascal Germain, François Laviolette, Jean-Francis Roy ; JMLR W&CP 33 :105-113, 2014

Random Bayesian networks with bounded indegree

Eunice Yuh-Jie Chen, Judea Pearl ; JMLR W&CP 33 :114-121, 2014

Efficient Low-Rank Stochastic Gradient Descent Methods for Solving Semidefinite Programs

Jianhui Chen, Tianbao Yang, Shenghuo Zhu ; JMLR W&CP 33 :122-130, 2014

Characterizing EVOI-Sufficient k-Response Query Sets in Decision Problems

Robert Cohn, Satinder Singh, Edmund Durfee ; JMLR W&CP 33 :131-139, 2014

Doubly Aggressive Selective Sampling Algorithms for Classification

Koby Crammer ; JMLR W&CP 33 :140-148, 2014

Sparse Bayesian Variable Selection for the Identification of Antigenic Variability in the Foot-and-Mouth Disease Virus

Vinny Davies, Richard Reeve, William Harvey, Francois Maree, Dirk Husmeier ; JMLR W&CP 33 :149-158, 2014

Sparsity and the truncated \(l^2\)-norm

Lee Dicker ; JMLR W&CP 33 :159-166, 2014

Efficient Distributed Topic Modeling with Provable Guarantees

Weicong Ding, Mohammad Rohban, Prakash Ishwar, Venkatesh Saligrama ; JMLR W&CP 33 :167-175, 2014

Pan-sharpening with a Bayesian nonparametric dictionary learning model

Xinghao Ding, Yiyong Jiang, Yue Huang, John Paisley ; JMLR W&CP 33 :176-184, 2014

Approximate Slice Sampling for Bayesian Posterior Inference

Christopher DuBois, Anoop Korattikara, Max Welling, Padhraic Smyth ; JMLR W&CP 33 :185-193, 2014

Bayesian Logistic Gaussian Process Models for Dynamic Networks

Daniele Durante, David Dunson ; JMLR W&CP 33 :194-201, 2014

Avoiding pathologies in very deep networks

David Duvenaud, Oren Rippel, Ryan Adams, Zoubin Ghahramani ; JMLR W&CP 33 :202-210, 2014

Efficient Inference for Complex Queries on Complex Distributions

Lili Dworkin, Michael Kearns, Lirong Xia ; JMLR W&CP 33 :211-219, 2014

Bayesian Switching Interaction Analysis Under Uncertainty

Zoran Dzunic, John Fisher III ; JMLR W&CP 33 :220-228, 2014

Robust learning of inhomogeneous PMMs

Ralf Eggeling, Teemu Roos, Petri Myllymäki, Ivo Grosse ; JMLR W&CP 33 :229-237, 2014

Fully-Automatic Bayesian Piecewise Sparse Linear Models

Riki Eto, Ryohei Fujimaki, Satoshi Morinaga, Hiroshi Tamano ; JMLR W&CP 33 :238-246, 2014

Learning with Maximum A-Posteriori Perturbation Models

Andreea Gane, Tamir Hazan, Tommi Jaakkola ; JMLR W&CP 33 :247-256, 2014

Sketching the Support of a Probability Measure

Joachim Giesen, Soeren Laue, Lars Kuehne ; JMLR W&CP 33 :257-265, 2014

Robust Stochastic Principal Component Analysis

John Goes, Teng Zhang, Raman Arora, Gilad Lerman ; JMLR W&CP 33 :266-274, 2014

Bayesian Nonparametric Poisson Factorization for Recommendation Systems

Prem Gopalan, Francisco J. Ruiz, Rajesh Ranganath, David Blei ; JMLR W&CP 33 :275-283, 2014

Efficiently Enforcing Diversity in Multi-Output Structured Prediction

Abner Guzman-Rivera, Pushmeet Kohli, Dhruv Batra, Rob Rutenbar ; JMLR W&CP 33 :284-292, 2014

Learning and Evaluation in Presence of Non-i.i.d. Label Noise

Nico Görnitz, Anne Porbadnigk, Alexander Binder, Claudia Sannelli, Mikio Braun, Klaus-Robert Mueller, Marius Kloft ; JMLR W&CP 33 :293-302, 2014

Analytic Long-Term Forecasting with Periodic Gaussian Processes

Nooshin HajiGhassemi, Marc Deisenroth ; JMLR W&CP 33 :303-311, 2014

On Estimating Causal Effects based on Supplemental Variables

Takahiro Hayashi, Manabu Kuroki ; JMLR W&CP 33 :312-319, 2014

Non-Asymptotic Analysis of Relational Learning with One Network

Peng He, Changshui Zhang ; JMLR W&CP 33 :320-327, 2014

Exploiting the Limits of Structure Learning via Inherent Symmetry

Peng He, Changshui Zhang ; JMLR W&CP 33 :328-337, 2014

A Statistical Model for Event Sequence Data

Kevin Heins, Hal Stern ; JMLR W&CP 33 :338-346, 2014

Probabilistic Solutions to Differential Equations and their Application to Riemannian Statistics

Philipp Hennig, Søren Hauberg ; JMLR W&CP 33 :347-355, 2014

Tilted Variational Bayes

James Hensman, Max Zwiessele, Neil Lawrence ; JMLR W&CP 33 :356-364, 2014

On correlation and budget constraints in model-based bandit optimization with application to automatic machine learning

Matthew Hoffman, Bobak Shahriari, Nando de Freitas ; JMLR W&CP 33 :365-374, 2014

Optimality of Thompson Sampling for Gaussian Bandits Depends on Priors

Junya Honda, Akimichi Takemura ; JMLR W&CP 33 :375-383, 2014

Tight Bounds for the Expected Risk of Linear Classifiers and PAC-Bayes Finite-Sample Guarantees

Jean Honorio, Tommi Jaakkola ; JMLR W&CP 33 :384-392, 2014

Latent Gaussian Models for Topic Modeling

Changwei Hu, Eunsu Ryu, David Carlson, Yingjian Wang, Lawrence Carin ; JMLR W&CP 33 :393-401, 2014

A Finite-Sample Generalization Bound for Semiparametric Regression: Partially Linear Models

Ruitong Huang, Csaba Szepesvari ; JMLR W&CP 33 :402-410, 2014

Global Optimization Methods for Extended Fisher Discriminant Analysis

Satoru Iwata, Yuji Nakatsukasa, Akiko Takeda ; JMLR W&CP 33 :411-419, 2014

High-Dimensional Density Ratio Estimation with Extensions to Approximate Likelihood Computation

Rafael Izbicki, Ann Lee, Chad Schafer ; JMLR W&CP 33 :420-429, 2014

Near Optimal Bayesian Active Learning for Decision Making

Shervin Javdani, Yuxin Chen, Amin Karbasi, Andreas Krause, Drew Bagnell, Siddhartha Srinivasa ; JMLR W&CP 33 :430-438, 2014

A Level-set Hit-and-run Sampler for Quasi-Concave Distributions

Shane Jensen, Dean Foster ; JMLR W&CP 33 :439-447, 2014

New Bounds on Compressive Linear Least Squares Regression

Ata Kaban ; JMLR W&CP 33 :448-456, 2014

Recovering Distributions from Gaussian RKHS Embeddings

Motonobu Kanagawa, Kenji Fukumizu ; JMLR W&CP 33 :457-465, 2014

Collaborative Ranking for Local Preferences

Berk Kapicioglu, David Rosenberg, Robert Schapire, Tony Jebara ; JMLR W&CP 33 :466-474, 2014

Scalable Collaborative Bayesian Preference Learning

Mohammad Emtiyaz Khan, Young Jun Ko, Matthias Seeger ; JMLR W&CP 33 :475-483, 2014

A Gaussian Latent Variable Model for Large Margin Classification of Labeled and Unlabeled Data

Do-kyum Kim, Matthew Der, Lawrence Saul ; JMLR W&CP 33 :484-492, 2014

Scalable Variational Bayesian Matrix Factorization with Side Information

Yong-Deok Kim, Seungjin Choi ; JMLR W&CP 33 :493-502, 2014

Algebraic Reconstruction Bounds and Explicit Inversion for Phase Retrieval at the Identifiability Threshold

Franz Király, Martin Ehler ; JMLR W&CP 33 :503-511, 2014

Visual Boundary Prediction: A Deep Neural Prediction Network and Quality Dissection

Jyri Kivinen, Chris Williams, Nicolas Heess ; JMLR W&CP 33 :512-521, 2014

Low-Rank Spectral Learning

Alex Kulesza, N. Raj Rao, Satinder Singh ; JMLR W&CP 33 :522-530, 2014

Fugue: Slow-Worker-Agnostic Distributed Learning for Big Models on Big Data

Abhimanu Kumar, Alex Beutel, Qirong Ho, Eric Xing ; JMLR W&CP 33 :531-539, 2014

Computational Education using Latent Structured Prediction

Tanja Käser, Alexander Schwing, Tamir Hazan, Markus Gross ; JMLR W&CP 33 :540-548, 2014

Towards building a Crowd-Sourced Sky Map

Dustin Lang, David Hogg, Bernhard Schölkopf ; JMLR W&CP 33 :549-557, 2014

Incremental Tree-Based Inference with Dependent Normalized Random Measures

Juho Lee, Seungjin Choi ; JMLR W&CP 33 :558-566, 2014

Jointly Informative Feature Selection

Leonidas Lefakis, Francois Fleuret ; JMLR W&CP 33 :567-575, 2014

Learning Heterogeneous Hidden Markov Random Fields

Jie Liu, Chunming Zhang, Elizabeth Burnside, David Page ; JMLR W&CP 33 :576-584, 2014

PAC-Bayesian Collective Stability

Ben London, Bert Huang, Ben Taskar, Lise Getoor ; JMLR W&CP 33 :585-594, 2014

Active Area Search via Bayesian Quadrature

Yifei Ma, Roman Garnett, Jeff Schneider ; JMLR W&CP 33 :595-603, 2014

Active Boundary Annotation using Random MAP Perturbations

Subhransu Maji, Tamir Hazan, Tommi Jaakkola ; JMLR W&CP 33 :604-613, 2014

Interpretable Sparse High-Order Boltzmann Machines

Martin Renqiang Min, Xia Ning, Chao Cheng, Mark Gerstein ; JMLR W&CP 33 :614-622, 2014

Efficient Lifting of MAP LP Relaxations Using k-Locality

Martin Mladenov, Kristian Kersting, Amir Globerson ; JMLR W&CP 33 :623-632, 2014

A Geometric Algorithm for Scalable Multiple Kernel Learning

John Moeller, Parasaran Raman, Suresh Venkatasubramanian, Avishek Saha ; JMLR W&CP 33 :633-642, 2014

On the Testability of Models with Missing Data

Karthika Mohan, Judea Pearl ; JMLR W&CP 33 :643-650, 2014

Selective Sampling with Drift

Edward Moroshko, Koby Crammer ; JMLR W&CP 33 :651-659, 2014

The Dependent Dirichlet Process Mixture of Objects for Detection-free Tracking and Object Modeling

Willie Neiswanger, Frank Wood, Eric Xing ; JMLR W&CP 33 :660-668, 2014

Bias Reduction and Metric Learning for Nearest-Neighbor Estimation of Kullback-Leibler Divergence

Yung-Kyun Noh, Masashi Sugiyama, Song Liu, Marthinus C. du Plessis, Frank Chongwoo Park, Daniel D. Lee ; JMLR W&CP 33 :669-677, 2014

Robust Forward Algorithms via PAC-Bayes and Laplace Distributions

Asaf Noy, Koby Crammer ; JMLR W&CP 33 :678-686, 2014

Joint Structure Learning of Multiple Non-Exchangeable Networks

Chris Oates, Sach Mukherjee ; JMLR W&CP 33 :687-695, 2014

Scaling Nonparametric Bayesian Inference via Subsample-Annealing

Fritz Obermeyer, Jonathan Glidden, Eric Jonas ; JMLR W&CP 33 :696-705, 2014

Fast Distribution To Real Regression

Junier Oliva, Willie Neiswanger, Barnabas Poczos, Jeff Schneider, Eric Xing ; JMLR W&CP 33 :706-714, 2014

FuSSO: Functional Shrinkage and Selection Operator

Junier Oliva, Barnabas Poczos, Timothy Verstynen, Aarti Singh, Jeff Schneider, Fang-Cheng Yeh, Wen-Yih Tseng ; JMLR W&CP 33 :715-723, 2014

To go deep or wide in learning?

Gaurav Pandey, Ambedkar Dukkipati ; JMLR W&CP 33 :724-732, 2014

LAMORE: A Stable, Scalable Approach to Latent Vector Autoregressive Modeling of Categorical Time Series

Yubin Park, Carlos Carvalho, Joydeep Ghosh ; JMLR W&CP 33 :733-742, 2014

Spoofing Large Probability Mass Functions to Improve Sampling Times and Reduce Memory Costs

Jon Parker, Hans Engler ; JMLR W&CP 33 :743-750, 2014

Learning Bounded Tree-width Bayesian Networks using Integer Linear Programming

Pekka Parviainen, Hossein Shahrabi Farahani, Jens Lagergren ; JMLR W&CP 33 :751-759, 2014

An Efficient Algorithm for Large Scale Compressive Feature Learning

Hristo Paskov, John Mitchell, Trevor Hastie ; JMLR W&CP 33 :760-768, 2014

Expectation Propagation for Likelihoods Depending on an Inner Product of Two Multivariate Random Variables

Tomi Peltola, Pasi Jylänki, Aki Vehtari ; JMLR W&CP 33 :769-777, 2014

An inclusion optimal algorithm for chain graph structure learning

Jose Peña, Dag Sonntag, Jens Nielsen ; JMLR W&CP 33 :778-786, 2014

A Stepwise uncertainty reduction approach to constrained global optimization

Victor Picheny ; JMLR W&CP 33 :787-795, 2014

Connected Sub-graph Detection

Jing Qian, Venkatesh Saligrama, Yuting Chen ; JMLR W&CP 33 :796-804, 2014

An Analysis of Active Learning with Uniform Feature Noise

Aaditya Ramdas, Barnabas Poczos, Aarti Singh, Larry Wasserman ; JMLR W&CP 33 :805-813, 2014

Black Box Variational Inference

Rajesh Ranganath, Sean Gerrish, David Blei ; JMLR W&CP 33 :814-822, 2014

Cluster Canonical Correlation Analysis

Nikhil Rasiwasia, Dhruv Mahajan, Vijay Mahadevan, Gaurav Aggarwal ; JMLR W&CP 33 :823-831, 2014

Sequential crowdsourced labeling as an epsilon-greedy exploration in a Markov Decision Process

Vikas Raykar, Priyanka Agrawal ; JMLR W&CP 33 :832-840, 2014

Learning Structured Models with the AUC Loss and Its Generalizations

Nir Rosenfeld, Ofer Meshi, Danny Tarlow, Amir Globerson ; JMLR W&CP 33 :841-849, 2014

Class Proportion Estimation with Application to Multiclass Anomaly Rejection

Tyler Sanderson, Clayton Scott ; JMLR W&CP 33 :850-858, 2014

Lifted MAP Inference for Markov Logic Networks

Somdeb Sarkhel, Deepak Venugopal, Parag Singla, Vibhav Gogate ; JMLR W&CP 33 :859-867, 2014

Estimating Dependency Structures for non-Gaussian Components with Linear and Energy Correlations

Hiroaki Sasaki, Michael Gutmann, Hayaru Shouno, Aapo Hyvarinen ; JMLR W&CP 33 :868-876, 2014

Student-t Processes as Alternatives to Gaussian Processes

Amar Shah, Andrew Wilson, Zoubin Ghahramani ; JMLR W&CP 33 :877-885, 2014

In Defense of Minhash over Simhash

Anshumali Shrivastava, Ping Li ; JMLR W&CP 33 :886-894, 2014

Loopy Belief Propagation in the Presence of Determinism

David Smith, Vibhav Gogate ; JMLR W&CP 33 :895-903, 2014

Explicit Link Between Periodic Covariance Functions and State Space Models

Arno Solin, Simo Särkkä ; JMLR W&CP 33 :904-912, 2014

Bat Call Identification with Gaussian Process Multinomial Probit Regression and a Dynamic Time Warping Kernel

Vassilios Stathopoulos, Veronica Zamora-Gutierrez, Kate Jones, Mark Girolami ; JMLR W&CP 33 :913-921, 2014

SMERED: A Bayesian Approach to Graphical Record Linkage and De-duplication

Rebecca Steorts, Rob Hall, Stephen Fienberg ; JMLR W&CP 33 :922-930, 2014

Adaptive Variable Clustering in Gaussian Graphical Models

Siqi Sun, Yuancheng Zhu, Jinbo Xu ; JMLR W&CP 33 :931-939, 2014

Scaling Graph-based Semi Supervised Learning to Large Number of Labels Using Count-Min Sketch

Partha Talukdar, William Cohen ; JMLR W&CP 33 :940-947, 2014

Path Thresholding: Asymptotically Tuning-Free High-Dimensional Sparse Regression

Divyanshu Vats, Richard Baraniuk ; JMLR W&CP 33 :948-957, 2014

Active Learning for Undirected Graphical Model Selection

Divyanshu Vats, Robert Nowak, Richard Baraniuk ; JMLR W&CP 33 :958-967, 2014

Linear-time training of nonlinear low-dimensional embeddings

Max Vladymyrov, Miguel Carreira-Perpinan ; JMLR W&CP 33 :968-977, 2014

Gaussian Copula Precision Estimation with Missing Values

Huahua Wang, Farideh Fazayeli, Soumyadeep Chatterjee, Arindam Banerjee ; JMLR W&CP 33 :978-986, 2014

An LP for Sequential Learning Under Budgets

Joseph Wang, Kirill Trapeznikov, Venkatesh Saligrama ; JMLR W&CP 33 :987-995, 2014

Efficient Algorithms and Error Analysis for the Modified Nystrom Method

Shusen Wang, Zhihua Zhang ; JMLR W&CP 33 :996-1004, 2014

Bayesian Multi-Scale Optimistic Optimization

Ziyu Wang, Babak Shakibi, Lin Jin, Nando de Freitas ; JMLR W&CP 33 :1005-1014, 2014

Accelerating ABC methods using Gaussian processes

Richard Wilkinson ; JMLR W&CP 33 :1015-1023, 2014

A New Approach to Probabilistic Programming Inference

Frank Wood, Jan Willem van de Meent, Vikash Mansinghka ; JMLR W&CP 33 :1024-1032, 2014

Dynamic Resource Allocation for Optimizing Population Diffusion

Shan Xue, Alan Fern, Daniel Sheldon ; JMLR W&CP 33 :1033-1041, 2014

Mixed Graphical Models via Exponential Families

Eunho Yang, Yulia Baker, Pradeep Ravikumar, Genevera Allen, Zhandong Liu ; JMLR W&CP 33 :1042-1050, 2014

Context Aware Group Nearest Shrunken Centroids in Large-Scale Genomic Studies

Juemin Yang, Fang Han, Rafael Irizarry, Han Liu ; JMLR W&CP 33 :1051-1059, 2014

Nonparametric estimation and testing of exchangeable graph models

Justin Yang, Christina Han, Edoardo Airoldi ; JMLR W&CP 33 :1060-1067, 2014

Generating Efficient MCMC Kernels from Probabilistic Programs

Lingfeng Yang, Patrick Hanrahan, Noah Goodman ; JMLR W&CP 33 :1068-1076, 2014

Efficient Transfer Learning Method for Automatic Hyperparameter Tuning

Dani Yogatama, Gideon Mann ; JMLR W&CP 33 :1077-1085, 2014

Accelerated Stochastic Gradient Method for Composite Regularization

Wenliang Zhong, James Kwok ; JMLR W&CP 33 :1086-1094, 2014

Heterogeneous Domain Adaptation for Multiple Classes

Joey Tianyi Zhou, Ivor W.Tsang, Sinno Jialin Pan, Mingkui Tan ; JMLR W&CP 33 :1095-1103, 2014