Bayesian learning of joint distributions of objects

Anjishnu Banerjee, Jared Murray, David Dunson; Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, PMLR 31:1-9

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Permutation estimation and minimax rates of identifiability

Olivier Collier, Arnak Dalalyan; Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, PMLR 31:10-19

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A unifying representation for a class of dependent random measures

Nicholas Foti, Joseph Futoma, Daniel Rockmore, Sinead Williamson; Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, PMLR 31:20-28

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Diagonal Orthant Multinomial Probit Models

James Johndrow, David Dunson, Kristian Lum; Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, PMLR 31:29-38

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Distributed Learning of Gaussian Graphical Models via Marginal Likelihoods

Zhaoshi Meng, Dennis Wei, Ami Wiesel, Alfred Hero III; Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, PMLR 31:39-47

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Sparse Principal Component Analysis for High Dimensional Multivariate Time Series

Zhaoran Wang, Fang Han, Han Liu; Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, PMLR 31:48-56

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A Competitive Test for Uniformity of Monotone Distributions

Jayadev Acharya, Ashkan Jafarpour, Alon Orlitsky, Ananda Suresh; Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, PMLR 31:57-65

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Clustering Oligarchies

Margareta Ackerman, Shai Ben-David, David Loker, Sivan Sabato; Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, PMLR 31:66-74

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Reconstructing ecological networks with hierarchical Bayesian regression and Mondrian processes

Andrej Aderhold, Dirk Husmeier, V. Anne Smith; Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, PMLR 31:75-84

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Nyström Approximation for Large-Scale Determinantal Processes

Raja Hafiz Affandi, Alex Kulesza, Emily Fox, Ben Taskar; Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, PMLR 31:85-98

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Further Optimal Regret Bounds for Thompson Sampling

Shipra Agrawal, Navin Goyal; Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, PMLR 31:99-107

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Distributed and Adaptive Darting Monte Carlo through Regenerations

Sungjin Ahn, Yutian Chen, Max Welling; Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, PMLR 31:108-116

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Consensus Ranking with Signed Permutations

Raman Arora, Marina Meilă; Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, PMLR 31:117-125

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Ultrahigh Dimensional Feature Screening via RKHS Embeddings

Krishnakumar Balasubramanian, Bharath Sriperumbudur, Guy Lebanon; Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, PMLR 31:126-134

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Meta-Transportability of Causal Effects: A Formal Approach

Elias Bareinboim, Judea Pearl; Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, PMLR 31:135-143

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Convex Collective Matrix Factorization

Guillaume Bouchard, Dawei Yin, Shengbo Guo; Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, PMLR 31:144-152

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Efficiently Sampling Probabilistic Programs via Program Analysis

Arun Chaganty, Aditya Nori, Sriram Rajamani; Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, PMLR 31:153-160

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Computing the M Most Probable Modes of a Graphical Model

Chao Chen, Vladimir Kolmogorov, Yan Zhu, Dimitris Metaxas, Christoph Lampert; Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, PMLR 31:161-169

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A simple criterion for controlling selection bias

Eunice Yuh-Jie Chen, Judea Pearl; Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, PMLR 31:170-177

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Evidence Estimation for Bayesian Partially Observed MRFs

Yutian Chen, Max Welling; Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, PMLR 31:178-186

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Why Steiner-tree type algorithms work for community detection

Mung Chiang, Henry Lam, Zhenming Liu, Vincent Poor; Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, PMLR 31:187-195

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A simple sketching algorithm for entropy estimation over streaming data

Peter Clifford, Ioana Cosma; Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, PMLR 31:196-206

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Deep Gaussian Processes

Andreas Damianou, Neil D. Lawrence; Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, PMLR 31:207-215

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ODE parameter inference using adaptive gradient matching with Gaussian processes

Frank Dondelinger, Dirk Husmeier, Simon Rogers, Maurizio Filippone; Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, PMLR 31:216-228

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Uncover Topic-Sensitive Information Diffusion Networks

Nan Du, Le Song, Hyenkyun Woo, Hongyuan Zha; Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, PMLR 31:229-237

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Stochastic blockmodeling of relational event dynamics

Christopher DuBois, Carter Butts, Padhraic Smyth; Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, PMLR 31:238-246

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Dynamic Copula Networks for Modeling Real-valued Time Series

Elad Eban, Gideon Rothschild, Adi Mizrahi, Israel Nelken, Gal Elidan; Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, PMLR 31:247-255

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Data-driven covariate selection for nonparametric estimation of causal effects

Doris Entner, Patrik Hoyer, Peter Spirtes; Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, PMLR 31:256-264

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Learning to Top-K Search using Pairwise Comparisons

Brian Eriksson; Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, PMLR 31:265-273

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

Hamed Firouzi, Bala Rajaratnam, Alfred Hero III; Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, PMLR 31:274-288

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Mixed LICORS: A Nonparametric Algorithm for Predictive State Reconstruction

Georg Goerg, Cosma Shalizi; Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, PMLR 31:289-297

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Unsupervised Link Selection in Networks

Quanquan Gu, Charu Aggarwal, Jiawei Han; Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, PMLR 31:298-306

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Clustered Support Vector Machines

Quanquan Gu, Jiawei Han; Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, PMLR 31:307-315

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

Abner Guzman-Rivera, Pushmeet Kohli, Dhruv Batra; Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, PMLR 31:316-324

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Recursive Karcher Expectation Estimators And Geometric Law of Large Numbers

Jeffrey Ho, Guang Cheng, Hesamoddin Salehian, Baba Vemuri; Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, PMLR 31:325-332

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DYNACARE: Dynamic Cardiac Arrest Risk Estimation

Joyce Ho, Yubin Park, Carlos Carvalho, Joydeep Ghosh; Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, PMLR 31:333-341

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Active Learning for Interactive Visualization

Tomoharu Iwata, Neil Houlsby, Zoubin Ghahramani; Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, PMLR 31:342-350

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

Prabhanjan Kambadur, Aurelie Lozano; Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, PMLR 31:351-359

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Beyond Sentiment: The Manifold of Human Emotions

Seungyeon Kim, Fuxin Li, Guy Lebanon, Irfan Essa; Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, PMLR 31:360-369

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Exact Learning of Bounded Tree-width Bayesian Networks

Janne Korhonen, Pekka Parviainen; Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, PMLR 31:370-378

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

Nevena Lazic, Christopher Bishop, John Winn; Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, PMLR 31:379-387

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Structure Learning of Mixed Graphical Models

Jason Lee, Trevor Hastie; Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, PMLR 31:388-396

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Dynamic Scaled Sampling for Deterministic Constraints

Lei Li, Bharath Ramsundar, Stuart Russell; Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, PMLR 31:397-405

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Learning Markov Networks With Arithmetic Circuits

Daniel Lowd, Amirmohammad Rooshenas; Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, PMLR 31:406-414

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

Heng Luo, Pierre Luc Carrier, Aaron Courville, Yoshua Bengio; Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, PMLR 31:415-423

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Fast Near-GRID Gaussian Process Regression

Yuancheng Luo, Ramani Duraiswami; Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, PMLR 31:424-432

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Estimating the Partition Function of Graphical Models Using Langevin Importance Sampling

Jianzhu Ma, Jian Peng, Sheng Wang, Jinbo Xu; Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, PMLR 31:433-441

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Thompson Sampling in Switching Environments with Bayesian Online Change Detection

Joseph Mellor, Jonathan Shapiro; Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, PMLR 31:442-450

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

Edward Moroshko, Koby Crammer; Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, PMLR 31:451-462

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Competing with an Infinite Set of Models in Reinforcement Learning

Phuong Nguyen, Odalric-Ambrym Maillard, Daniil Ryabko, Ronald Ortner; Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, PMLR 31:463-471

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Efficient Variational Inference for Gaussian Process Regression Networks

Trung Nguyen, Edwin Bonilla; Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, PMLR 31:472-480

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High-dimensional Inference via Lipschitz Sparsity-Yielding Regularizers

Zheng Pan, Changshui Zhang; Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, PMLR 31:481-488

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Bayesian Structure Learning for Functional Neuroimaging

Mijung Park, Oluwasanmi Koyejo, Joydeep Ghosh, Russell Poldrack, Jonathan Pillow; Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, PMLR 31:489-497

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Random Projections for Support Vector Machines

Saurabh Paul, Christos Boutsidis, Malik Magdon-Ismail, Petros Drineas; Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, PMLR 31:498-506

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Distribution-Free Distribution Regression

Barnabas Poczos, Aarti Singh, Alessandro Rinaldo, Larry Wasserman; Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, PMLR 31:507-515

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Localization and Adaptation in Online Learning

Alexander Rakhlin, Ohad Shamir, Karthik Sridharan; Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, PMLR 31:516-526

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A recursive estimate for the predictive likelihood in a topic model

James Scott, Jason Baldridge; Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, PMLR 31:527-535

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Detecting Activations over Graphs using Spanning Tree Wavelet Bases

James Sharpnack, Aarti Singh, Akshay Krishnamurthy; Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, PMLR 31:536-544

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Changepoint Detection over Graphs with the Spectral Scan Statistic

James Sharpnack, Aarti Singh, Alessandro Rinaldo; Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, PMLR 31:545-553

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Central Limit Theorems for Conditional Markov Chains

Mathieu Sinn, Bei Chen; Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, PMLR 31:554-562

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Statistical Tests for Contagion in Observational Social Network Studies

Greg Ver Steeg, Aram Galstyan; Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, PMLR 31:563-571

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Completeness Results for Lifted Variable Elimination

Nima Taghipour, Daan Fierens, Guy Van den Broeck, Jesse Davis, Hendrik Blockeel; Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, PMLR 31:572-580

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Supervised Sequential Classification Under Budget Constraints

Kirill Trapeznikov, Venkatesh Saligrama; Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, PMLR 31:581-589

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On the Asymptotic Optimality of Maximum Margin Bayesian Networks

Sebastian Tschiatschek, Franz Pernkopf; Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, PMLR 31:590-598

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Collapsed Variational Bayesian Inference for Hidden Markov Models

Pengyu Wang, Phil Blunsom; Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, PMLR 31:599-607

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Block Regularized Lasso for Multivariate Multi-Response Linear Regression

Weiguang Wang, Yingbin Liang, Eric Xing; Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, PMLR 31:608-617

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Bethe Bounds and Approximating the Global Optimum

Adrian Weller, Tony Jebara; Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, PMLR 31:618-631

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Dual Decomposition for Joint Discrete-Continuous Optimization

Christopher Zach; Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, PMLR 31:632-640

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

Ke Zhou, Hongyuan Zha, Le Song; Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, PMLR 31:641-649

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Greedy Bilateral Sketch, Completion & Smoothing

Tianyi Zhou, Dacheng Tao; Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, PMLR 31:650-658

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Scoring anomalies: a M-estimation formulation

Stéphan Clémençon, Jérémie Jakubowicz; Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, PMLR 31:659-667

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