UAI 2017

92 papers

A Fast Algorithm for Matrix Eigen-Decomposition Zhiqiang Xu, Yiping Ke, Xin Gao

A Practical Method for Solving Contextual Bandit Problems Using Decision Trees Adam N. Elmachtoub, Ryan McNellis, Sechan Oh, Marek Petrik

A Probabilistic Framework for Multi-Label Learning with Unseen Labels Abhilash Gaure, Aishwarya Gupta, Vinay Kumar Verma, Piyush Rai

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

A Tractable Probabilistic Model for Subset Selection Yujia Shen, Arthur Choi, Adnan Darwiche

Adversarial Sets for Regularising Neural Link Predictors Pasquale Minervini, Thomas Demeester, Tim Rocktäschel, Sebastian Riedel

Algebraic Equivalence Class Selection for Linear Structural Equation Models Thijs van Ommen, Joris M. Mooij

An Efficient Minibatch Acceptance Test for Metropolis-Hastings Daniel Seita, Xinlei Pan, Haoyu Chen, John F. Canny

Analysis of Thompson Sampling for Stochastic Sleeping Bandits Aritra Chatterjee, Ganesh Ghalme, Shweta Jain, Rohit Vaish, Y. Narahari

Approximate Evidential Reasoning Using Local Conditioning and Conditional Belief Functions Van Nguyen

Approximation Complexity of Maximum a Posteriori Inference in Sum-Product Networks Diarmaid Conaty, Cassio P. de Campos, Denis Deratani Mauá

AutoGP: Exploring the Capabilities and Limitations of Gaussian Process Models Karl Krauth, Edwin V. Bonilla, Kurt Cutajar, Maurizio Filippone

Balanced Mini-Batch Sampling for SGD Using Determinantal Point Processes Cheng Zhang, Hedvig Kjellström, Stephan Mandt

Bayesian Inference of Log Determinants Jack K. Fitzsimons, Kurt Cutajar, Maurizio Filippone, Michael A. Osborne, Stephen J. Roberts

Branch and Bound for Regular Bayesian Network Structure Learing Joe Suzuki, Jun Kawahara

Causal Consistency of Structural Equation Models Paul K. Rubenstein, Sebastian Weichwald, Stephan Bongers, Joris M. Mooij, Dominik Janzing, Moritz Grosse-Wentrup, Bernhard Schölkopf

Causal Discovery from Temporally Aggregated Time Series Mingming Gong, Kun Zhang, Bernhard Schölkopf, Clark Glymour, Dacheng Tao

Communication-Efficient Distributed Primal-Dual Algorithm for Saddle Point Problem Yaodong Yu, Sulin Liu, Sinno Jialin Pan

Complexity of Solving Decision Trees with Skew-Symmetric Bilinear Utility Hugo Gilbert, Olivier Spanjaard

Composing Inference Algorithms as Program Transformations Robert Zinkov, Chung-chieh Shan

Computing Nonvacuous Generalization Bounds for Deep (Stochastic) Neural Networks with Many More Parameters than Training Data Gintare Karolina Dziugaite, Daniel M. Roy

Continuously Tempered Hamiltonian Monte Carlo Matthew M. Graham, Amos J. Storkey

Convex-Constrained Sparse Additive Modeling and Its Extensions Junming Yin, Yaoliang Yu

Counting Markov Equivalence Classes by Number of Immoralities Adityanarayanan Radhakrishnan, Liam Solus, Caroline Uhler

Coupling Adaptive Batch Sizes with Learning Rates Lukas Balles, Javier Romero, Philipp Hennig

Data-Dependent Sparsity for Subspace Clustering Bo Xin, Yizhou Wang, Wen Gao, David P. Wipf

Decoupling Homophily and Reciprocity with Latent Space Network Models Jiasen Yang, Vinayak A. Rao, Jennifer Neville

Differentially Private Variational Inference for Non-Conjugate Models Joonas Jälkö, Antti Honkela, Onur Dikmen

Effective Sketching Methods for Value Function Approximation Yangchen Pan, Erfan Sadeqi Azer, Martha White

Efficient Online Learning for Optimizing Value of Information: Theory and Application to Interactive Troubleshooting Yuxin Chen, Jean-Michel Renders, Morteza Haghir Chehreghani, Andreas Krause

Efficient Solutions for Stochastic Shortest Path Problems with Dead Ends Felipe W. Trevizan, Florent Teichteil-Königsbuch, Sylvie Thiébaux

Embedding Senses via Dictionary Bootstrapping Byungkon Kang, Kyung-Ah Sohn

Exact Inference for Relational Graphical Models with Interpreted Functions: Lifted Probabilistic Inference Modulo Theories Rodrigo de Salvo Braz, Ciaran O'Reilly

Fair Optimal Stopping Policy for Matching with Mediator Yang Liu

Fast Amortized Inference and Learning in Log-Linear Models with Randomly Perturbed Nearest Neighbor Search Stephen Mussmann, Daniel Levy, Stefano Ermon

Feature-to-Feature Regression for a Two-Step Conditional Independence Test Qinyi Zhang, Sarah Filippi, Seth R. Flaxman, Dino Sejdinovic

FROSH: FasteR Online Sketching Hashing Xixian Chen, Irwin King, Michael R. Lyu

Green Generative Modeling: Recycling Dirty Data Using Recurrent Variational Autoencoders Yu Wang, Bin Dai, Gang Hua, John A. D. Aston, David P. Wipf

Holographic Feature Representations of Deep Networks Martin A. Zinkevich, Alex Davies, Dale Schuurmans

How Good Are My Predictions? Efficiently Approximating Precision-Recall Curves for Massive Datasets Ashish Sabharwal, Hanie Sedghi

Hybrid Deep Discriminative/Generative Models for Semi-Supervised Learning Volodymyr Kuleshov, Stefano Ermon

Importance Sampled Stochastic Optimization for Variational Inference Joseph Sakaya, Arto Klami

Importance Sampling for Fair Policy Selection Shayan Doroudi, Philip S. Thomas, Emma Brunskill

Improving Optimization-Based Approximate Inference by Clamping Variables Junyao Zhao, Josip Djolonga, Sebastian Tschiatschek, Andreas Krause

Intelligent Robots in an Uncertain World Leslie Pack Kaelbling

Interpreting and Using CPDAGs with Background Knowledge Emilija Perkovic, Markus Kalisch, Marloes H. Maathuis

Interpreting Lion Behaviour as Probabilistic Programs Neil Dhir, Matthijs Vákár, Matthew Wijers, Andrew Markham, Frank D. Wood

Inverse Reinforcement Learning via Deep Gaussian Process Ming Jin, Andreas C. Damianou, Pieter Abbeel, Costas J. Spanos

Iterative Decomposition Guided Variable Neighborhood Search for Graphical Model Energy Minimization Abdelkader Ouali, David Allouche, Simon de Givry, Samir Loudni, Yahia Lebbah, Lakhdar Loukil

Learning and Inference with Expectations Amir Globerson

Learning Approximately Objective Priors Eric T. Nalisnick, Padhraic Smyth

Learning the Structure of Probabilistic Sentential Decision Diagrams Yitao Liang, Jessa Bekker, Guy Van den Broeck

Learning to Acquire Information Yewen Pu, Leslie Pack Kaelbling, Armando Solar-Lezama

Learning to Draw Samples with Amortized Stein Variational Gradient Descent Yihao Feng, Dilin Wang, Qiang Liu

Learning Treatment-Response Models from Multivariate Longitudinal Data Hossein Soleimani, Adarsh Subbaswamy, Suchi Saria

Learning with Confident Examples: Rank Pruning for Robust Classification with Noisy Labels Curtis G. Northcutt, Tailin Wu, Isaac L. Chuang

Machine Learning for Healthcare Data Katherine A. Heller

Monte-Carlo Tree Search Using Batch Value of Perfect Information Shahaf S. Shperberg, Solomon Eyal Shimony, Ariel Felner

Multi-Dueling Bandits with Dependent Arms Yanan Sui, Vincent Zhuang, Joel W. Burdick, Yisong Yue

Near-Optimal Interdiction of Factored MDPs Swetasudha Panda, Yevgeniy Vorobeychik

Near-Orthogonality Regularization in Kernel Methods Pengtao Xie, Barnabás Póczos, Eric P. Xing

Neighborhood Regularized ℓ1-Graph Yingzhen Yang, Jiashi Feng, Jiahui Yu, Jianchao Yang, Thomas S. Huang

On Loopy Belief Propagation - Local Stability Analysis for Non-Vanishing Fields Christian Knoll, Franz Pernkopf

On the Complexity of Nash Equilibrium Reoptimization Andrea Celli, Alberto Marchesi, Nicola Gatti

Online Constrained Model-Based Reinforcement Learning Benjamin van Niekerk, Andreas C. Damianou, Benjamin Rosman

Probabilistic Program Abstractions Steven Holtzen, Todd D. Millstein, Guy Van den Broeck

Provable Inductive Robust PCA via Iterative Hard Thresholding U. N. Niranjan, Arun Rajkumar, Theja Tulabandhula

Real-Time Resource Allocation for Tracking Systems Yash Satsangi, Shimon Whiteson, Frans A. Oliehoek, Henri Bouma

Regret Minimization Algorithms for the Followers Behaviour Identification in Leadership Games Lorenzo Bisi, Giuseppe De Nittis, Francesco Trovò, Marcello Restelli, Nicola Gatti

Robust Model Equivalence Using Stochastic Bisimulation for N-Agent Interactive DIDs Muthukumaran Chandrasekaran, Junhuan Zhang, Prashant Doshi, Yifeng Zeng

Safe Semi-Supervised Learning of Sum-Product Networks Martin Trapp, Tamas Madl, Robert Peharz, Franz Pernkopf, Robert Trappl

SAT-Based Causal Discovery Under Weaker Assumptions Zhalama, Jiji Zhang, Frederick Eberhardt, Wolfgang Mayer

Self-Discrepancy Conditional Independence Test Sanghack Lee, Vasant G. Honavar

Shortest Path Under Uncertainty: Exploration Versus Exploitation Zhan Wei Lim, David Hsu, Wee Sun Lee

Snorkel: Beyond Hand-Labeled Data Christopher Ré

Stein Variational Adaptive Importance Sampling Jun Han, Qiang Liu

Stein Variational Policy Gradient Yang Liu, Prajit Ramachandran, Qiang Liu, Jian Peng

Stochastic Bandit Models for Delayed Conversions Claire Vernade, Olivier Cappé, Vianney Perchet

Stochastic L-BFGS Revisited: Improved Convergence Rates and Practical Acceleration Strategies Renbo Zhao, William B. Haskell, Vincent Y. F. Tan

Stochastic Segmentation Trees for Multiple Ground Truths Jake Snell, Richard S. Zemel

Structure Learning of Linear Gaussian Structural Equation Models with Weak Edges Marco Eigenmann, Preetam Nandy, Marloes H. Maathuis

Submodular Variational Inference for Network Reconstruction Lin Chen, Forrest W. Crawford, Amin Karbasi

Supervised Restricted Boltzmann Machines Tu Dinh Nguyen, Dinh Q. Phung, Viet Huynh, Trung Le

Synthesis of Strategies in Influence Diagrams Manuel Luque, Manuel Arias, Francisco Javier Díez

The Binomial Block Bootstrap Estimator for Evaluating Loss on Dependent Clusters Matt Barnes, Artur Dubrawski

The Total Belief Theorem Chunlai Zhou, Fabio Cuzzolin

Towards Conditional Independence Test for Relational Data Sanghack Lee, Vasant G. Honavar

Triply Stochastic Gradients on Multiple Kernel Learning Xiang Li, Bin Gu, Shuang Ao, Huaimin Wang, Charles X. Ling

Two Current Analysis Challenges: Single Cell Omics and Nanopore Long-Read Sequence Data Terry Speed

Value Directed Exploration in Multi-Armed Bandits with Structured Priors Bence Cserna, Marek Petrik, Reazul Hasan Russel, Wheeler Ruml

Weighted Model Counting with Function Symbols Vaishak Belle

Why Rules Are Complex: Real-Valued Probabilistic Logic Programs Are Not Fully Expressive David Buchman, David Poole