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Editors: Carlos M. Carvalho, Pradeep Ravikumar
Bayesian learning of joint distributions of objects
; 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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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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