A Fast Stochastic Riemannian Eigensolver

Zhiqiang Xu, Yiping Ke, Xin Gao; Proceedings of the 33rd Conference on Uncertainty in Artificial Intelligence, PMLR R15:1-10

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A Kernel Conditional Independence Test for Relational Data

Sanghack Lee, Vasant Honavar; Proceedings of the 33rd Conference on Uncertainty in Artificial Intelligence, PMLR R15:11-20

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A Practical Method for Solving Contextual Bandit Problems Using Decision Trees

Adam N. Elmachtoub, Ryan McNellis, Sechan Oh, Marek Petrik; Proceedings of the 33rd Conference on Uncertainty in Artificial Intelligence, PMLR R15:21-30

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A Probabilistic Framework for Zero-Shot Multi-Label Learning

Abhilash Gaure, Aishwarya Gupta, Vinay Kumar Verma, Piyush Rai; Proceedings of the 33rd Conference on Uncertainty in Artificial Intelligence, PMLR R15:31-40

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A Reinforcement Learning Approach to Weaning of Mechanical Ventilation in Intensive Care Units

Niranjani Prasad, Li-Fang Cheng, Corey Chivers, Michael Draugelis, Barbara E Engelhardt; Proceedings of the 33rd Conference on Uncertainty in Artificial Intelligence, PMLR R15:41-50

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A Tractable Probabilistic Model for Subset Selection

Yujia Shen, Arthur Choi, Adnan Darwiche; Proceedings of the 33rd Conference on Uncertainty in Artificial Intelligence, PMLR R15:51-60

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Adversarial Sets for Regularising Neural Link Predictors

Pasquale Minervini, Thomas Demeester, Tim Rocktäschel, Sebastian Riedel; Proceedings of the 33rd Conference on Uncertainty in Artificial Intelligence, PMLR R15:61-70

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Algebraic Equivalence of Linear Structural Equation Models

Thijs van Ommen, Joris M. Mooij; Proceedings of the 33rd Conference on Uncertainty in Artificial Intelligence, PMLR R15:71-80

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Best Student Paper Honorable Mention

An Efficient Minibatch Acceptance Test for Metropolis-Hastings

Daniel Seita, Xinlei Pan, Haoyu Chen, John Canny; Proceedings of the 33rd Conference on Uncertainty in Artificial Intelligence, PMLR R15:81-90

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Analysis of Thompson Sampling for Stochastic Sleeping Bandits

Aritra Chatterjee, Ganesh Ghalme, Shweta Jain, Rohit Vaish, Y. Narahari; Proceedings of the 33rd Conference on Uncertainty in Artificial Intelligence, PMLR R15:91-100

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Approximate Evidential Reasoning Using Local Conditioning and Conditional Belief Functions

Van Nguyen; Proceedings of the 33rd Conference on Uncertainty in Artificial Intelligence, PMLR R15:101-110

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Approximation Complexity of Maximum A Posteriori Inference in Sum-Product Networks

Diarmaid Conaty, Denis D. Maua, Cassio P. de Campos; Proceedings of the 33rd Conference on Uncertainty in Artificial Intelligence, PMLR R15:111-120

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AutoGP: Exploring the Capabilities and Limitations of Gaussian Process Models

Karl Krauth, Edwin V. Bonilla, Kurt Cutajar, Maurizio Filippone; Proceedings of the 33rd Conference on Uncertainty in Artificial Intelligence, PMLR R15:121-130

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Bayesian Inference of Log Determinants

J Fitzsimons, K Cutajar, M Filippone, M Osborne, S Roberts; Proceedings of the 33rd Conference on Uncertainty in Artificial Intelligence, PMLR R15:131-140

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Branch and Bound for Regular Bayesian Network Structure Learning

Joe Suzuki, Jun Kawahara; Proceedings of the 33rd Conference on Uncertainty in Artificial Intelligence, PMLR R15:141-150

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Causal Consistency of Structural Equation Models

Paul K. Rubenstein*, Sebastian Weichwald*, Stephan Bongers, Joris M. Mooij, Dominik Janzing, Moritz Grosse-Wentrup, Bernhard Schoelkopf; Proceedings of the 33rd Conference on Uncertainty in Artificial Intelligence, PMLR R15:151-160

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Causal Discovery from Temporally Aggregated Time Series

Mingming Gong, Kun Zhang, Bernhard Schölkopf, Clark Glymour, Dacheng Tao; Proceedings of the 33rd Conference on Uncertainty in Artificial Intelligence, PMLR R15:161-170

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Communication-Efficient Distributed Primal-Dual Algorithm for Saddle Point Problems

Yaodong Yu, Sulin Liu, Sinno Jialin Pan; Proceedings of the 33rd Conference on Uncertainty in Artificial Intelligence, PMLR R15:171-180

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Complexity of Solving Decision Trees with Skew-Symmetric Bilinear Utility

Hugo Gilbert, Olivier Spanjaard; Proceedings of the 33rd Conference on Uncertainty in Artificial Intelligence, PMLR R15:181-190

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Composing inference algorithms as program transformations

Robert Zinkov, Chung-chieh Shan; Proceedings of the 33rd Conference on Uncertainty in Artificial Intelligence, PMLR R15:191-200

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Computing Nonvacuous Generalization Bounds for Deep (Stochastic) Neural Networks with Many More Parameters than Training Data

Gintare Karolina Dziugaite, Daniel M. Roy; Proceedings of the 33rd Conference on Uncertainty in Artificial Intelligence, PMLR R15:201-210

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Continuously tempered Hamiltonian Monte Carlo

Matthew M. Graham, Amos J. Storkey; Proceedings of the 33rd Conference on Uncertainty in Artificial Intelligence, PMLR R15:211-220

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Convex-constrained Sparse Additive Modeling and Its Extensions

Junming Yin, Yaoliang Yu; Proceedings of the 33rd Conference on Uncertainty in Artificial Intelligence, PMLR R15:221-230

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Counting Markov Equivalence Classes by Number of Immoralities

Adityanarayanan Radhakrishnan, Liam Solus, Caroline Uhler; Proceedings of the 33rd Conference on Uncertainty in Artificial Intelligence, PMLR R15:231-240

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Coupling Adaptive Batch Sizes with Learning Rates

Lukas Balles, Javier Romero, Philipp Hennig; Proceedings of the 33rd Conference on Uncertainty in Artificial Intelligence, PMLR R15:241-250

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Data-Dependent Sparsity for Subspace Clustering

Bo Xin, Yizhou Wang, Wen Gao, David Wipf; Proceedings of the 33rd Conference on Uncertainty in Artificial Intelligence, PMLR R15:251-260

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Decoupling Homophily and Reciprocity with Latent Space Network Models

Jiasen Yang, Vinayak Rao, Jennifer Neville; Proceedings of the 33rd Conference on Uncertainty in Artificial Intelligence, PMLR R15:261-270

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Deep Hybrid Models: Bridging Discriminative and Generative Approaches

Volodymyr Kuleshov, Stefano Ermon; Proceedings of the 33rd Conference on Uncertainty in Artificial Intelligence, PMLR R15:271-280

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Determinantal Point Processes for Mini-Batch Diversification

Cheng Zhang, Hedvig Kjellstrom, Stephan Mandt; Proceedings of the 33rd Conference on Uncertainty in Artificial Intelligence, PMLR R15:281-290

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Differentially Private Variational Inference for Non-conjugate Models

Joonas Jälkö, Onur Dikmen, Antti Honkela; Proceedings of the 33rd Conference on Uncertainty in Artificial Intelligence, PMLR R15:291-300

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Effective sketching methods for value function approximation

Yangchen Pan, Erfan Sadeqi Azer, Martha White; Proceedings of the 33rd Conference on Uncertainty in Artificial Intelligence, PMLR R15:301-310

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Efficient Online Learning for Optimizing Value of Information: Theory and Application to Interactive Troubleshooting

Yuxin Chen, Jean-Michel Renders, Morteza Haghir Chehreghani, Andreas Krause; Proceedings of the 33rd Conference on Uncertainty in Artificial Intelligence, PMLR R15:311-320

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Efficient solutions for Stochastic Shortest Path Problems with Dead Ends

Felipe Trevizan, Florent Teichteil-Königsbuch, Sylvie Thiebaux; Proceedings of the 33rd Conference on Uncertainty in Artificial Intelligence, PMLR R15:321-330

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Embedding Senses via Dictionary Bootstrapping

Byungkon Kang, Kyung-Ah Sohn; Proceedings of the 33rd Conference on Uncertainty in Artificial Intelligence, PMLR R15:331-340

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Exact Inference for Relational Graphical Models with Interpreted Functions: Lifted Probabilistic Inference Modulo Theories

Rodrigo de Salvo Braz, Ciaran O’Reilly; Proceedings of the 33rd Conference on Uncertainty in Artificial Intelligence, PMLR R15:341-350

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FROSH: FasteR Online Sketching Hashing

Xixian Chen, Irwin King, Michael R. Lyu; Proceedings of the 33rd Conference on Uncertainty in Artificial Intelligence, PMLR R15:351-360

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Fair Optimal Stopping Policy for Matching with Mediator

Yang Liu; Proceedings of the 33rd Conference on Uncertainty in Artificial Intelligence, PMLR R15:361-370

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Fast Amortized Inference and Learning in Log-linear Models with Randomly Perturbed Nearest Neighbor Search

Stephen Mussmann, Daniel Levy, Stefano Ermon; Proceedings of the 33rd Conference on Uncertainty in Artificial Intelligence, PMLR R15:371-380

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Feature-to-Feature Regression for a Two-Step Conditional Independence Test

Qinyi Zhang, Sarah Filippi, Seth Flaxman, Dino Sejdinovic; Proceedings of the 33rd Conference on Uncertainty in Artificial Intelligence, PMLR R15:381-390

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Green Generative Modeling: Recycling Dirty Data using Recurrent Variational Autoencoders

Yu Wang, Bin Dai, Gang Hua, John Aston, David Wipf; Proceedings of the 33rd Conference on Uncertainty in Artificial Intelligence, PMLR R15:391-400

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Holographic Feature Representations of Deep Networks

Martin A. Zinkevich, Alex Davies, Dale Schuurmans; Proceedings of the 33rd Conference on Uncertainty in Artificial Intelligence, PMLR R15:401-410

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How Good Are My Predictions? Efficiently Approximating Precision-Recall Curves for Massive Datasets

Ashish Sabharwal, Hanie Sedghi; Proceedings of the 33rd Conference on Uncertainty in Artificial Intelligence, PMLR R15:411-420

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Importance Sampled Stochastic Optimization for Variational Inference

Joseph Sakaya, Arto Klami; Proceedings of the 33rd Conference on Uncertainty in Artificial Intelligence, PMLR R15:421-430

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Importance Sampling for Fair Policy Selection

Shayan Doroudi, Philip Thomas, Emma Brunskill; Proceedings of the 33rd Conference on Uncertainty in Artificial Intelligence, PMLR R15:431-440

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Improving Optimization-Based Approximate Inference by Clamping Variables

Junyao Zhao, Josip Djolonga, Sebastian Tschiatschek, Andreas Krause; Proceedings of the 33rd Conference on Uncertainty in Artificial Intelligence, PMLR R15:441-450

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Interpreting Lion Behaviour with Nonparametric Probabilistic Programs

Neil Dhir, Matthijs Vákár, Matthew Wijers, Andrew Markham, Frank Wood, Paul Trethowan, Byron Du Preez, Andrew Loveridge, David MacDonald; Proceedings of the 33rd Conference on Uncertainty in Artificial Intelligence, PMLR R15:451-460

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Interpreting and using CPDAGs with background knowledge

Emilija Perkovic, Markus Kalisch, Marloes H. Maathuis; Proceedings of the 33rd Conference on Uncertainty in Artificial Intelligence, PMLR R15:461-470

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Inverse Reinforcement Learning via Deep Gaussian Process

Ming Jin, Andreas Damianou, Pieter Abbeel, Costas Spanos; Proceedings of the 33rd Conference on Uncertainty in Artificial Intelligence, PMLR R15:471-480

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Iterative Decomposition Guided Variable Neighborhood Search for Graphical Model Energy Minimization

Abdelkader Ouali, David Allouche, Simon de Givry, Samir Loudni, Yahia Lebbah, Francisco Eckhardt, Lakhdar Loukil; Proceedings of the 33rd Conference on Uncertainty in Artificial Intelligence, PMLR R15:481-490

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Learning Approximately Objective Priors

Eric Nalisnick, Padhraic Smyth; Proceedings of the 33rd Conference on Uncertainty in Artificial Intelligence, PMLR R15:491-500

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Learning the Structure of Probabilistic Sentential Decision Diagrams

Yitao Liang, Jessa Bekker, Guy Van den Broeck; Proceedings of the 33rd Conference on Uncertainty in Artificial Intelligence, PMLR R15:501-510

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Learning to Acquire Information

Yewen Pu, Leslie Pack Kaelbling, Armando Solar-Lezama; Proceedings of the 33rd Conference on Uncertainty in Artificial Intelligence, PMLR R15:511-520

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Learning to Draw Samples with Amortized Stein Variational Gradient Descent

Yihao Feng, Dilin Wang, Qiang Liu; Proceedings of the 33rd Conference on Uncertainty in Artificial Intelligence, PMLR R15:521-530

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Learning with Confident Examples: Rank Pruning for Robust Classification with Noisy Labels

Curtis G. Northcutt, Tailin Wu, Isaac L. Chuang; Proceedings of the 33rd Conference on Uncertainty in Artificial Intelligence, PMLR R15:531-540

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Monte-Carlo Tree Search using Batch Value of Perfect Information

Shahaf S. Shperberg, Solomon Eyal Shimony, Ariel Felner; Proceedings of the 33rd Conference on Uncertainty in Artificial Intelligence, PMLR R15:541-550

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Multi-dueling Bandits with Dependent Arms

Yanan Sui, Vincent Zhuang, Joel W. Burdick, Yisong Yue; Proceedings of the 33rd Conference on Uncertainty in Artificial Intelligence, PMLR R15:551-560

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Near-Optimal Interdiction of Factored MDPs

Swetasudha Panda, Yevgeniy Vorobeychik; Proceedings of the 33rd Conference on Uncertainty in Artificial Intelligence, PMLR R15:561-570

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Near-Orthogonality Regularization in Kernel Methods

Pengtao Xie, Barnabas Poczos, Eric Xing; Proceedings of the 33rd Conference on Uncertainty in Artificial Intelligence, PMLR R15:571-580

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Neighborhood Regularized $\ell^1$-Graph

Yingzhen Yang, Jiashi Feng, Jiahui Yu, Jianchao Yang, Pushmeet Kohli, Thomas S. Huang; Proceedings of the 33rd Conference on Uncertainty in Artificial Intelligence, PMLR R15:581-590

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On Loopy Belief Propagation – Local Stability Analysis for Non-Vanishing Fields

Christian Knoll, Franz Pernkopf; Proceedings of the 33rd Conference on Uncertainty in Artificial Intelligence, PMLR R15:591-600

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On the Complexity of Nash Equilibrium Reoptimization

Andrea Celli, Alberto Marchesi, Nicola Gatti; Proceedings of the 33rd Conference on Uncertainty in Artificial Intelligence, PMLR R15:601-610

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Online Constrained Model-based Reinforcement Learning

Benjamin van Niekerk, Andreas Damianou, Benjamin Rosman; Proceedings of the 33rd Conference on Uncertainty in Artificial Intelligence, PMLR R15:611-620

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Probabilistic Program Abstractions

Steven Holtzen, Todd Millstein, Guy Van den Broeck; Proceedings of the 33rd Conference on Uncertainty in Artificial Intelligence, PMLR R15:621-630

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Provable Inductive Robust PCA via Iterative Hard Thresholding

U.N. Niranjan, Arun Rajkumar, Theja Tulabandhula; Proceedings of the 33rd Conference on Uncertainty in Artificial Intelligence, PMLR R15:631-640

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Real-Time Resource Allocation for Tracking Systems

Yash Satsangi, Shimon Whiteson, Frans A. Oliehoek, Henri Bouma; Proceedings of the 33rd Conference on Uncertainty in Artificial Intelligence, PMLR R15:641-650

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Regret Minimization Algorithms for the Follower’s Behaviour Identification in Leadership Games

Lorenzo Bisi, Giuseppe De Nittis, Francesco Trov‘ò, Marcello Restelli, Nicola Gatti; Proceedings of the 33rd Conference on Uncertainty in Artificial Intelligence, PMLR R15:651-660

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Robust Model Equivalence using Stochastic Bisimulation for N-Agent Interactive DIDs

Muthukumaran Chandrasekaran, Junhuan Zhang, Prashant Doshi, Yifeng Zeng; Proceedings of the 33rd Conference on Uncertainty in Artificial Intelligence, PMLR R15:661-670

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SAT-Based Causal Discovery under Weaker Assumptions

Zhalama, Jiji Zhang, Frederick Eberhardt, Wolfgang Mayer; Proceedings of the 33rd Conference on Uncertainty in Artificial Intelligence, PMLR R15:671-680

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Safe Semi-Supervised Learning of Sum-Product Networks

Martin Trapp, Tamas Madl, Robert Peharz, Franz Pernkopf, Robert Trappl; Proceedings of the 33rd Conference on Uncertainty in Artificial Intelligence, PMLR R15:681-690

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Self-Discrepancy Conditional Independence Test

Sanghack Lee, Vasant Honavar; Proceedings of the 33rd Conference on Uncertainty in Artificial Intelligence, PMLR R15:691-700

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Shortest Path under Uncertainty: Exploration versus Exploitation

Zhan Wei Lim, David Hsu, Wee Sun Lee; Proceedings of the 33rd Conference on Uncertainty in Artificial Intelligence, PMLR R15:701-710

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Stein Variational Adaptive Importance Sampling

Jun Han, Qiang Liu; Proceedings of the 33rd Conference on Uncertainty in Artificial Intelligence, PMLR R15:711-720

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Stein Variational Policy Gradient

Yang Liu, Prajit Ramachandran, Qiang Liu, Jian Peng; Proceedings of the 33rd Conference on Uncertainty in Artificial Intelligence, PMLR R15:721-729

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Stochastic Bandit Models for Delayed Conversions

Claire Vernade, Olivier Cappé, Vianney Perchet; Proceedings of the 33rd Conference on Uncertainty in Artificial Intelligence, PMLR R15:730-739

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Stochastic L-BFGS Revisited: Improved Convergence Rates and Practical Acceleration Strategies

Renbo Zhao, William B. Haskell, Vincent Y. F. Tan; Proceedings of the 33rd Conference on Uncertainty in Artificial Intelligence, PMLR R15:740-749

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Stochastic Segmentation Trees for Multiple Ground Truths

Jake Snell, Richard S. Zemel; Proceedings of the 33rd Conference on Uncertainty in Artificial Intelligence, PMLR R15:750-759

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Structure Learning of Linear Gaussian Structural Equation Models with Weak Edges

Marco Eigenmann, Preetam Nandy, Marloes Maathuis; Proceedings of the 33rd Conference on Uncertainty in Artificial Intelligence, PMLR R15:760-769

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Submodular Variational Inference for Network Reconstruction

Lin Chen, Forrest W. Crawford, Amin Karbasi; Proceedings of the 33rd Conference on Uncertainty in Artificial Intelligence, PMLR R15:770-779

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Supervised Restricted Boltzmann Machines

Tu Dinh Nguyen, Dinh Phung, Viet Huynh, Trung Le; Proceedings of the 33rd Conference on Uncertainty in Artificial Intelligence, PMLR R15:780-789

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Synthesis of strategies in influence diagrams

Manuel Luque, Manuel Arias, Francisco Javier Díez; Proceedings of the 33rd Conference on Uncertainty in Artificial Intelligence, PMLR R15:790-798

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The Binomial Block Bootstrap Estimator for Evaluating Loss on Dependent Clusters

Matt Barnes, Artur Dubrawski; Proceedings of the 33rd Conference on Uncertainty in Artificial Intelligence, PMLR R15:799-808

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The total belief theorem

Chunlai Zhou, Fabio Cuzzolin; Proceedings of the 33rd Conference on Uncertainty in Artificial Intelligence, PMLR R15:809-818

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Treatment-Response Models for Counterfactual Reasoning with Continuous-time, Continuous-valued Interventions

Hossein Soleimani, Adarsh Subbaswamy, Suchi Saria; Proceedings of the 33rd Conference on Uncertainty in Artificial Intelligence, PMLR R15:819-828

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Triply Stochastic Gradients on Multiple Kernel Learning

Xiang Li, Bin Gu, Shuang Ao, Huaimin Wang, Charles X. Ling; Proceedings of the 33rd Conference on Uncertainty in Artificial Intelligence, PMLR R15:829-837

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Value Directed Exploration in Multi-Armed Bandits with Structured Priors

Bence Cserna, Marek Petrik, Reazul Hasan Russel, Wheeler Ruml; Proceedings of the 33rd Conference on Uncertainty in Artificial Intelligence, PMLR R15:838-847

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Weighted Model Counting With Function Symbols

Vaishak Belle; Proceedings of the 33rd Conference on Uncertainty in Artificial Intelligence, PMLR R15:848-857

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Best Student Paper

Why Rules are Complex: Real-Valued Probabilistic Logic Programs are not Fully Expressive

David Buchman, David Poole; Proceedings of the 33rd Conference on Uncertainty in Artificial Intelligence, PMLR R15:858-867

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