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JMLR Workshop and Conference Proceedings

Volume 31 : Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics

Editors: Carvalho, Carlos M. and Ravikumar, Pradeep


Part I: Notable Papers

Bayesian learning of joint distributions of objects

Anjishnu Banerjee, Jared Murray, David Dunson ; JMLR W&CP 31:1–9, 2013

Permutation estimation and minimax rates of identifiability

Olivier Collier, Arnak Dalalyan ; JMLR W&CP 31:10–19, 2013

A unifying representation for a class of dependent random measures

Nicholas Foti, Joseph Futoma, Daniel Rockmore, Sinead Williamson ; JMLR W&CP 31:20–28, 2013

Diagonal Orthant Multinomial Probit Models

James Johndrow, David Dunson, Kristian Lum ; JMLR W&CP 31:29–38, 2013

Distributed Learning of Gaussian Graphical Models via Marginal Likelihoods

Zhaoshi Meng, Dennis Wei, Ami Wiesel, Alfred Hero III ; JMLR W&CP 31:39–47, 2013

Sparse Principal Component Analysis for High Dimensional Multivariate Time Series

Zhaoran Wang, Fang Han, Han Liu ; JMLR W&CP 31:48–56, 2013

Part II: Regular Papers

A Competitive Test for Uniformity of Monotone Distributions

Jayadev Acharya, Ashkan Jafarpour, Alon Orlitsky, Ananda Suresh ; JMLR W&CP 31:57–65, 2013

Clustering Oligarchies

Margareta Ackerman, Shai Ben-David, David Loker, Sivan Sabato ; JMLR W&CP 31:66–74, 2013

Reconstructing ecological networks with hierarchical Bayesian regression and Mondrian processes

Andrej Aderhold, Dirk Husmeier, V. Anne Smith ; JMLR W&CP 31:75–84, 2013

Nystrom Approximation for Large-Scale Determinantal Processes

Raja Hafiz Affandi, Alex Kulesza, Emily Fox, Ben Taskar ; JMLR W&CP 31:85–98, 2013

Further Optimal Regret Bounds for Thompson Sampling

Shipra Agrawal, Navin Goyal ; JMLR W&CP 31:99–107, 2013

Distributed and Adaptive Darting Monte Carlo through Regenerations

Sungjin Ahn, Yutian Chen, Max Welling ; JMLR W&CP 31:108–116, 2013

Consensus Ranking with Signed Permutations

Raman Arora, Marina Meila ; JMLR W&CP 31:117–125, 2013

Ultrahigh Dimensional Feature Screening via RKHS Embeddings

Krishnakumar Balasubramanian, Bharath Sriperumbudur, Guy Lebanon ; JMLR W&CP 31:126–134, 2013

Meta-Transportability of Causal Effects: A Formal Approach

Elias Bareinboim, Judea Pearl ; JMLR W&CP 31:135–143, 2013

Convex Collective Matrix Factorization

Guillaume Bouchard, Dawei Yin, Shengbo Guo ; JMLR W&CP 31:144–152, 2013

Efficiently Sampling Probabilistic Programs via Program Analysis

Arun Chaganty, Aditya Nori, Sriram Rajamani ; JMLR W&CP 31:153–160, 2013

Computing the M Most Probable Modes of a Graphical Model

Chao Chen, Vladimir Kolmogorov, Yan Zhu, Dimitris Metaxas, Christoph Lampert ; JMLR W&CP 31:161–169, 2013

A simple criterion for controlling selection bias

Eunice Yuh-Jie Chen, Judea Pearl ; JMLR W&CP 31:170–177, 2013

Evidence Estimation for Bayesian Partially Observed MRFs

Yutian Chen, Max Welling ; JMLR W&CP 31:178–186, 2013

Why Steiner-tree type algorithms work for community detection

Mung Chiang, Henry Lam, Zhenming Liu, Vincent Poor ; JMLR W&CP 31:187–195, 2013

A simple sketching algorithm for entropy estimation over streaming data

Peter Clifford, Ioana Cosma ; JMLR W&CP 31:196–206, 2013

Deep Gaussian Processes

Andreas Damianou, Neil Lawrence ; JMLR W&CP 31:207–215, 2013

ODE parameter inference using adaptive gradient matching with Gaussian processes

Frank Dondelinger, Dirk Husmeier, Simon Rogers, Maurizio Filippone ; JMLR W&CP 31:216–228, 2013

Uncover Topic-Sensitive Information Diffusion Networks

Nan Du, Le Song, Hyenkyun Woo, Hongyuan Zha ; JMLR W&CP 31:229–237, 2013

Stochastic blockmodeling of relational event dynamics

Christopher DuBois, Carter Butts, Padhraic Smyth ; JMLR W&CP 31:238–246, 2013

Dynamic Copula Networks for Modeling Real-valued Time Series

Elad Eban, Gideon Rothschild, Adi Mizrahi, Israel Nelken, Gal Elidan ; JMLR W&CP 31:247–255, 2013

Data-driven covariate selection for nonparametric estimation of causal effects

Doris Entner, Patrik Hoyer, Peter Spirtes ; JMLR W&CP 31:256–264, 2013

Learning to Top-K Search using Pairwise Comparisons

Brian Eriksson ; JMLR W&CP 31:265–273, 2013

Predictive Correlation Screening: Application to Two-stage Predictor Design in High Dimension

Hamed Firouzi, Bala Rajaratnam, Alfred Hero III ; JMLR W&CP 31:274–288, 2013

Mixed LICORS: A Nonparametric Algorithm for Predictive State Reconstruction

Georg Goerg, Cosma Shalizi ; JMLR W&CP 31:289–297, 2013

Unsupervised Link Selection in Networks

Quanquan Gu, Charu Aggarwal, Jiawei Han ; JMLR W&CP 31:298–306, 2013

Clustered Support Vector Machines

Quanquan Gu, Jiawei Han ; JMLR W&CP 31:307–315, 2013

DivMCuts: Faster Training of Structural SVMs with Diverse M-Best Cutting-Planes

Abner Guzman-Rivera, Pushmeet Kohli, Dhruv Batra ; JMLR W&CP 31:316–324, 2013

Recursive Karcher Expectation Estimators And Geometric Law of Large Numbers

Jeffrey Ho, Guang Cheng, Hesamoddin Salehian, Baba Vemuri ; JMLR W&CP 31:325–332, 2013

DYNACARE: Dynamic Cardiac Arrest Risk Estimation

Joyce Ho, Yubin Park, Carlos Carvalho, Joydeep Ghosh ; JMLR W&CP 31:333–341, 2013

Active Learning for Interactive Visualization

Tomoharu Iwata, Neil Houlsby, Zoubin Ghahramani ; JMLR W&CP 31:342–350, 2013

A Parallel, Block Greedy Method for Sparse Inverse Covariance Estimation for Ultra-high Dimensions

Prabhanjan Kambadur, Aurelie Lozano ; JMLR W&CP 31:351–359, 2013

Beyond Sentiment: The Manifold of Human Emotions

Seungyeon Kim, Fuxin Li, Guy Lebanon, Irfan Essa ; JMLR W&CP 31:360–369, 2013

Exact Learning of Bounded Tree-width Bayesian Networks

Janne Korhonen, Pekka Parviainen ; JMLR W&CP 31:370–378, 2013

Structural Expectation Propagation (SEP): Bayesian structure learning for networks with latent variables

Nevena Lazic, Christopher Bishop, John Winn ; JMLR W&CP 31:379–387, 2013

Structure Learning of Mixed Graphical Models

Jason Lee, Trevor Hastie ; JMLR W&CP 31:388–396, 2013

Dynamic Scaled Sampling for Deterministic Constraints

Lei Li, Bharath Ramsundar, Stuart Russell ; JMLR W&CP 31:397–405, 2013

Learning Markov Networks With Arithmetic Circuits

Daniel Lowd, Amirmohammad Rooshenas ; JMLR W&CP 31:406–414, 2013

Texture Modeling with Convolutional Spike-and-Slab RBMs and Deep Extensions

Heng Luo, Pierre Luc Carrier, Aaron Courville, Yoshua Bengio ; JMLR W&CP 31:415–423, 2013

Fast Near-GRID Gaussian Process Regression

Yuancheng Luo, Ramani Duraiswami ; JMLR W&CP 31:424–432, 2013

Estimating the Partition Function of Graphical Models Using Langevin Importance Sampling

Jianzhu Ma, Jian Peng, Sheng Wang, Jinbo Xu ; JMLR W&CP 31:433–441, 2013

Thompson Sampling in Switching Environments with Bayesian Online Change Detection

Joseph Mellor, Jonathan Shapiro ; JMLR W&CP 31:442–450, 2013

A Last-Step Regression Algorithm for Non-Stationary Online Learning

Edward Moroshko, Koby Crammer ; JMLR W&CP 31:451–462, 2013

Competing with an Infinite Set of Models in Reinforcement Learning

Phuong Nguyen, Odalric-Ambrym Maillard, Daniil Ryabko, Ronald Ortner ; JMLR W&CP 31:463–471, 2013

Efficient Variational Inference for Gaussian Process Regression Networks

Trung Nguyen, Edwin Bonilla ; JMLR W&CP 31:472–480, 2013

High-dimensional Inference via Lipschitz Sparsity-Yielding Regularizers

Zheng Pan, Changshui Zhang ; JMLR W&CP 31:481–488, 2013

Bayesian Structure Learning for Functional Neuroimaging

Mijung Park, Oluwasanmi Koyejo, Joydeep Ghosh, Russell Poldrack, Jonathan Pillow ; JMLR W&CP 31:489–497, 2013

Random Projections for Support Vector Machines

Saurabh Paul, Christos Boutsidis, Malik Magdon-Ismail, Petros Drineas ; JMLR W&CP 31:498–506, 2013

Distribution-Free Distribution Regression

Barnabas Poczos, Aarti Singh, Alessandro Rinaldo, Larry Wasserman ; JMLR W&CP 31:507–515, 2013

Localization and Adaptation in Online Learning

Alexander Rakhlin, Ohad Shamir, Karthik Sridharan ; JMLR W&CP 31:516–526, 2013

A recursive estimate for the predictive likelihood in a topic model

James Scott, Jason Baldridge ; JMLR W&CP 31:527–535, 2013

Detecting Activations over Graphs using Spanning Tree Wavelet Bases

James Sharpnack, Aarti Singh, Akshay Krishnamurthy ; JMLR W&CP 31:536–544, 2013

Changepoint Detection over Graphs with the Spectral Scan Statistic

James Sharpnack, Aarti Singh, Alessandro Rinaldo ; JMLR W&CP 31:545–553, 2013

Central Limit Theorems for Conditional Markov Chains

Mathieu Sinn, Bei Chen ; JMLR W&CP 31:554–562, 2013

Statistical Tests for Contagion in Observational Social Network Studies

Greg Ver Steeg, Aram Galstyan ; JMLR W&CP 31:563–571, 2013

Completeness Results for Lifted Variable Elimination

Nima Taghipour, Daan Fierens, Guy Van den Broeck, Jesse Davis, Hendrik Blockeel ; JMLR W&CP 31:572–580, 2013

Supervised Sequential Classification Under Budget Constraints

Kirill Trapeznikov, Venkatesh Saligrama ; JMLR W&CP 31:581–589, 2013

On the Asymptotic Optimality of Maximum Margin Bayesian Networks

Sebastian Tschiatschek, Franz Pernkopf ; JMLR W&CP 31:590–598, 2013

Collapsed Variational Bayesian Inference for Hidden Markov Models

Pengyu Wang, Phil Blunsom ; JMLR W&CP 31:599–607, 2013

Block Regularized Lasso for Multivariate Multi-Response Linear Regression

Weiguang Wang, Yingbin Liang, Eric Xing ; JMLR W&CP 31:608–617, 2013

Bethe Bounds and Approximating the Global Optimum

Adrian Weller, Tony Jebara ; JMLR W&CP 31:618–631, 2013

Dual Decomposition for Joint Discrete-Continuous Optimization

Christopher Zach ; JMLR W&CP 31:632–640, 2013

Learning Social Infectivity in Sparse Low-rank Networks Using Multi-dimensional Hawkes Processes

Ke Zhou, Hongyuan Zha, Le Song ; JMLR W&CP 31:641–649, 2013

Greedy Bilateral Sketch, Completion & Smoothing

Tianyi Zhou, Dacheng Tao ; JMLR W&CP 31:650–658, 2013

Scoring anomalies: a M-estimation formulation

Stéphan Clémençon, Jérémie Jakubowicz ; JMLR W&CP 31:659–667, 2013