UAI 2019 - Accepted Papers

ID: 1

Personalized Peer Truth Serum for Eliciting Multi-Attribute Personal Data

Naman Goel, Boi Faltings
ID: 6

Conditional Expectation Propagation

Zheng Wang, Shandian Zhe
ID: 7

A Sparse Representation-Based Approach to Linear Regression with Partially Shuffled Labels

Martin Slawski, Mostafa Rahmani, Ping Li
ID: 13

On Fast Convergence of Proximal Algorithms for SQRT-Lasso Optimization: Don’t Worry About its Nonsmooth Loss Function

Xingguo Li, Haoming Jiang, Jarvis Haupt, Raman Arora, Han Liu, Mingyi Hong, Tuo Zhao
ID: 14

Correlated Fictitious Play for Aggregation Systems

Tanvi Verma, Pradeep Varakantham
ID: 15

Causal Calculus in the Presence of Cycles, Latent Confounders and Selection Bias

Patrick Forré, Joris M. Mooij
ID: 16

Variational Regret Bounds for Reinforcement Learning

Pratik Gajane, Ronald Ortner, Peter Auer
ID: 17

Recommendation from Raw Data with Adaptive Compound Poisson Factorization

Olivier Gouvert, Thomas Oberlin, Cédric Févotte
ID: 19

One-Shot Inference in Markov Random Fields

Hao Xiong, Yuanzhen Guo, Yibo Yang, Nicholas Ruozzi
ID: 21

Truly Proximal Policy Optimization

Yuhui Wang, Hao He, Xiaoyang Tan
ID: 24

Learning Factored Markov Decision Processes with Unawareness

Craig Innes, Alex Lascarides
ID: 25

Expressive Priors in Bayesian Neural Networks: Kernel Combinations and Periodic Functions

Tim Pearce, Mohamed Zaki, Alexandra Brintrup, Andy Neely
ID: 28

Countdown Regression: Sharp and Calibrated Survival Predictions

Anand Avati, Tony Duan, Sharon Zhou, Ken Jung, Nigam H. Shah, Andrew Ng
ID: 32

Reducing Exploration of Dying Arms in Mortal Bandits

Stefano Tracà, Weiyu Yan, Cynthia Rudin
ID: 33

Comparing EM with GD in Mixture Models of Two Components

Guojun Zhang, Pascal Poupart, George Trimponias
ID: 35

Efficient Search-Based Weighted Model Integration

Zhe Zeng, Guy Van den Broeck
ID: 45

Causal Discovery with General Non-Linear Relationships using Non-Linear ICA

Ricardo Pio Monti, Kun Zhang, Aapo Hyvarinen
ID: 47

BubbleRank: Safe Online Learning to Re-Rank via Implicit Click Feedback

Chang Li, Branislav Kveton, Tor Lattimore, Ilya Markov, Maarten de Rijke, Csaba Szepesvari, Masrour Zoghi
ID: 49

Coordinating Users of Shared Facilities via Predictive Assistants: Algorithms and Game-theoretic Analysis

Philipp Geiger, Michel Besserve, Justus Winkelmann, Claudius Proissl, Bernhard Schoelkopf
ID: 53

The Incomplete Rosetta Stone Problem: Identifiability Results for Multi-View Nonlinear ICA

Luigi Gresele, Paul Rubenstein, Arash Mehrjou, Francesco Locatello, Bernhard Schoelkopf
ID: 55

Random Clique Covers for Graphs with Local Density and Global Sparsity

Sinead A. Williamson, Mauricio Tec
ID: 64

Randomized Iterative Algorithms for Fisher Discriminant Analysis

Agniva Chowdhury, Jiasen Yang, Petros Drineas
ID: 78

Dynamic Trip-Vehicle Dispatch with Scheduled and On-Demand Requests

Taoan Huang, Bohui Fang, Hoon Oh, Xiaohui Bei, Fei Fang
ID: 83

Fall of Emperor: Breaking Defenses of Byzantine-Tolerant SGD

Cong Xie, Oluwasanmi Koyejo, Indranil Gupta
ID: 86

Regular LDPC Construction for Sparse Hashing

Jonathan Kuck, Tri Dao, Shenjia Zhao, Burak Bartan, Ashish Sabharwal, Stefano Ermon
ID: 91

Towards a Better Understanding and Regularization of the GAN Training Dynamics

Weili Nie, Ankit Patel
ID: 101

Domain Generalization via Multi-Domain Discriminant Analysis

Shoubo Hu, Kun Zhang, Zhitang Chen, Laiwan Chan
ID: 112

Efficient Planning Under Uncertainty with Incremental Refinement

Juan Carlos Saborío, Joachim Hertzberg
ID: 118

Cubic Regularization with Momentum for Nonconvex Optimization

Zhe Wang, Yi Zhou, Yingbin Liang, Guanghui Lan
ID: 122

Stability of Linear Structural Equation Models of Causal Inference

Navin Goyal, Anand Louis, Karthik Abinav Sankararaman
ID: 124

Random Sum-Product Networks: A Simple and Effective Approach to Probabilistic Deep Learning

Robert Peharz, Antonio Vergari, Karl Stelzner, Alejandro Molina, Martin Trapp, Xiaoting Shao, Kristian Kersting, Zoubin Ghahramani
ID: 127

Towards Robust Relational Causal Discovery

Sanghack Lee, Vasant Honavar
ID: 128

The Role of Memory in Stochastic Optimization

Antonio Orvieto, Jonas Kohler, Aurelien Lucchi
ID: 129

Random Search and Reproducibility for Neural Architecture Search

Liam Li, Ameet Talwalkar
ID: 138

Joint Nonparametric Precision Matrix Estimation with Confounding

Sinong Geng, Mladen Kolar, Oluwasanmi Koyejo
ID: 144

General Identifiability with Arbitrary Surrogate Experiments

Sanghack Lee, Juan D. Correa, Elias Bareinboim
ID: 148

Differentiable Probabilistic Models of Scientific Imaging with the Fourier Slice Theorem

Karen Ullrich, Rianne van den Berg, Marcus A. Brubaker, David Fleet, Max Welling
ID: 152

Approximate Inference in Structured Instances with Noisy Categorical Observations

Alireza Heidari, Ihab F. Ilyas, Theodoros Rekatsinas
ID: 156

Randomized Value Functions via Multiplicative Normalizing Flows

Ahmed Touati, Harsh Satija, Joshua Romoff, Joelle Pineau, Pascal Vincent
ID: 158

A Fast Proximal Point Method for Computing Exact Wasserstein Distance

Yujia Xie, Xiangfeng Wang, Ruijia Wang, Hongyuan Zha
ID: 159

Neural Dynamics Discovery via Gaussian Process Recurrent Neural Networks

Qi She, Anqi Wu
ID: 161

Fisher-Bures Adversary Graph Convolutional Networks

Ke Sun, Piotr Koniusz, Jeff Wang
ID: 162

Epsilon-BMC: A Bayesian Ensemble Approach to Epsilon-Greedy Exploration in Model-Free Reinforcement Learning

Michael Gimelfarb, Scott Sanner, Chi-Guhn Lee
ID: 163

Periodic Kernel Approximation by Index Set Fourier Series Features

Anthony Tompkins, Fabio Ramos
ID: 164

Scaling Tight Relaxations for Neural Network Verification

Krishnamurthy (Dj) Dvijotham, Robert Stanforth, Soham De, Sven Gowal, Chongli Qin, Pushmeet Kohli
ID: 172

Augmenting and Tuning Knowledge Graph Embeddings

Farnood Salehi, Robert Bamler, Stephan Mandt
ID: 174

A Tighter Analysis of Randomised Policy Iteration

Meet Taraviya, Shivaram Kalyanakrishnan
ID: 176

Perturbed-History Exploration in Stochastic Linear Bandits

Branislav Kveton, Csaba Szepesvari, Mohammad Ghavamzadeh, Craig Boutilier
ID: 191

A Sharp Convergence Analysis of Stochastic Variance-Reduced Policy Gradient

Pan Xu, Felicia Gao, Quanquan Gu
ID: 192

Deep Mixture of Experts via Shallow Embedding

Xin Wang, Fisher Yu, Lisa Dunlap, Yi-An Ma, Ruth Wang, Azalia Mirhoseini, Trevor Darrell, Joseph E. Gonzalez
ID: 193

Sampling-Free Variational Inference of Bayesian Neural Networks by Variance Backpropagation

Manuel Haussmann, Fred A. Hamprecht, Melih Kandemir
ID: 204

Sliced Score Matching

Yang Song, Sahaj Garg, Jiaxin Shi, Stefano Ermon
ID: 205

Causal Constraints Models

Tineke Blom, Joris M. Mooij
ID: 206

MAB with Graphs: A Graph Coloring Approach for Regret Minimization

Aadirupa Saha, Shreyas Sheshadri, Chiranjib Bhattacharyya
ID: 210

Approximate Causal Abstractions

Sander Beckers, Frederick Eberhardt, Joseph Y. Halpern
ID: 213

The Sensitivity of Counterfactual Fairness to Unmeasured Confounding

Niki Kilbertus, Matt Kusner, Adrian Weller, Ricardo Silva
ID: 221

Belief Propagation: Accurate Marginals or Accurate Partition Function -- Where is the Difference?

Christian Knoll, Franz Pernkopf
ID: 222

Finding Minimal d-separators in Linear Time and Applications

Benito van der Zander, Maciej Liśkiewicz
ID: 228

A Bayesian Approach to Robust Reinforcement Learning

Esther Derman, Daniel J. Mankowitz, Timothy A. Mann, Shie Mannor
ID: 232

A Universal Algorithm for Online Convex Optimization

Guanghui Wang, Shiyin Lu, Lijun Zhang
ID: 234

Evacuate or Not? A POMDP Model of the Decision Making of Individuals in Hurricane Evacuation Zones

Adithya Raam Sankar, Prashant Doshi, Adam Goodie
ID: 235

Probabilistic Programming for Birth-Death Models of Evolution Using an Alive Particle Filter with Delayed sampling

Jan Kudlicka, Lawrence M. Murray, Fredrik Ronquist, Thomas B. Schön
ID: 239

Variational Sparse Coding

Francesco Tonolini, Bjørn Sand Jensen, Roderick Murray-Smith
ID: 244

Learning with Non-Convex Truncated Losses by SGD

Yi Xu, Shenghuo Zhu, Sen Yang, Chi Zhang, Rong Jin, Tianbao Yang
ID: 245

Active Multi-Information Source Bayesian Quadrature

Alexandra Gessner, Javier Gonzalez, Maren Mahsereci
ID: 248

Cascade Linear Submodular Bandits: Accounting for Position Bias and Diversity in Online Learning to Rank

Harvineet Singh, Gaurush Hiranandani, Prakhar Gupta, Iftikhar Ahamath Burhanuddin, Zheng Wen, Branislav Kveton
ID: 253

Sinkhorn AutoEncoders

Giorgio Patrini, Rianne van den Berg, Patrick Forré, Marcello Carioni, Samarth Bhargav, Max Welling, Tim Genewein, Frank Nielsen
ID: 262

How to Exploit Structure while Solving Weighted Model Integration Problems

Pedro Zuidberg Dos Martires, Samuel Kolb, Luc De Raedt
ID: 264

Multi-Class Gaussian Process Classification Made Conjugate: Efficient Inference via Data Augmentation

Théo Galy-Fajou, Florian Wenzel, Christian Donner, Manfred Opper
ID: 267

A Flexible Framework for Multi-Objective Bayesian Optimization using Random Scalarizations

Biswajit Paria, Kirthevasan Kandasamy, Barnabás Póczos
ID: 275

Efficient Multitask Feature and Relationship Learning

Han Zhao, Otilia Stretcu, Alex Smola, Geoff Gordon
ID: 284

Practical Multi-Fidelity Bayesian Optimization of Iterative Machine Learning Algorithms

Jian Wu, Saul Toscano-Palmerin, Peter I. Frazier, Andrew Gordon Wilson
ID: 290

Adaptively Truncating Backpropagation Through Time to Control Gradient Bias

Christopher Aicher, Nicholas J. Foti, Emily B. Fox
ID: 296

Sampling-free Uncertainty Estimation in Gated Recurrent Units with Applications to Normative Modeling in Neuroimaging

Seong Jae Hwang, Ronak Mehta, Hyunwoo Kim, Vikas Singh
ID: 299

Online Factorization and Partition of Complex Networks by Random Walk

Lin F. Yang, Zheng Yu, Vladimir Braverman, Tuo Zhao, Mengdi Wang
ID: 302

On Densification for Minwise Hashing

Tung Mai, Anup Rao, Matt Kapilevich, Ryan Rossi, Yasin Abbsi Yadkori, Ritwik Sinha
ID: 310

N-GCN: Multi-Scale Graph Convolution for Semi-Supervised Node Classification

Sami Abu-El-Haija, Amol Kapoor, Bryan Perozzi, Joonseok Lee
ID: 312

Problem-dependent Regret Bounds for Online Learning with Feedback Graph

Bingshan Hu, Nishant A. Mehta, Jianping Pan
ID: 315

Wasserstein Fair Classification

Ray Jiang, Aldo Pacchiano, Heinrich Jiang, Tom Stepleton, Silvia Chiappa
ID: 317

Variational Training for Large-Scale Noisy-Or Bayesian Networks

Geng Ji, Dehua Cheng, Huazhong Ning, Changhe Yuan, Hanning Zhou, Liang Xiong, Erik Sudderth
ID: 319

Guaranteed Scalable Learning of Latent Tree Models

Furong Huang, Niranjan UN, Ioakeim Perros, Robert Chen, Jimeng Sun, Anima Anandkumar
ID: 324

On First-Order Bounds, Variance and Gap-Dependent Bounds for Adversarial Bandits

Roman Pogodin, Tor Lattimore
ID: 332

Reliable Uncertainty Estimates in Neural Networks using Noise Contrastive Priors

Danijar Hafner, Dustin Tran, Timothy Lillicrap, Alex Irpan, James Davidson
ID: 334

Fake It Till You Make It: Learning-Compatible Performance Support

Jonathan Bragg, Emma Brunskill
ID: 335

Interpreting Humans Literally is More Robust for Objective Learning

Smitha Milli, Anca D. Dragan
ID: 339

Convergence Analysis of Gradient-Based Learning in Continuous Games

Benjamin Chasnov, Lillian Ratliff, Eric Mazumdar, Sam Burden
ID: 340

End-to-end Training of Deep Probabilistic CCA on Paired Biomedical Observations

Gregory Gundersen, Bianca Dumitrascu, Jordan T. Ash, Barbara E. Engelhardt
ID: 341

Approximate Relative Value Learning for Average-Reward Continuous State MDPs

Hiteshi Sharma, Mehdi Jafarnia-Jahromi, Rahul Jain
ID: 345

Exact Sampling of Directed Acyclic Graphs from Modular Distributions

Topi Talvitie, Aleksis Vuoksenmaa, Mikko Koivisto
ID: 352

Intervening on Network Ties

Eli Sherman, Ilya Shpitser
ID: 356

Generating and Sampling Orbits for Lifted Probabilistic Inference

Steven Holtzen, Todd Millstein, Guy Van den Broeck
ID: 368

Real-Time Robotic Search using Hierarchical Spatial Point Processes

Olov Andersson, Per Sidén, Johan Dahlin, Patrick Doherty, Mattias Villani
ID: 370

Learning Intervention for True News Diffusion to Combat Fake News Spread using Deep Reinforcement Learning

Mahak Goindani, Jennifer Neville
ID: 371

P3O: Policy-On Policy-Off Policy Optimization

Rasool Fakoor, Pratik Chaudhari, Alex Smola
ID: 372

Causal Inference Under Interference and Network Uncertainty

Rohit Bhattacharya, Daniel Malinsky, Ilya Shpitser
ID: 373

Revisiting Reweighted Wake-Sleep for Models with Stochastic Control Flow

Tuan Anh Le, Adam R. Kosiorek, N. Siddharth, Yee Whye Teh, Frank Wood
ID: 380

Learnability for the Information Bottleneck

Tailin Wu, Max Tegmark, Isaac Chuang, Ian Fischer
ID: 383

Learning Belief Representations for Imitation Learning in POMDPs

Tanmay Gangwani, Joel Lehman, Qiang Liu, Jian Peng
ID: 393

Object Conditioning for Causal Inference

David Jensen, Javier Burroni, Matthew Rattigan
ID: 403

Conditional Mutual Information Estimation with Applications to Conditional Independence Testing

Sudipto Mukherjee, Himanshu Asnani, Sreeram Kannan
ID: 406

Parametric Mechanism Design under Uncertainty

Enrique Areyan Viqueira, Cyrus Cousins, Yasser Mohammad, Eli Upfal, Amy Greenwald
ID: 407

On the Relationship Between Satisfiability and Markov Decision Processes

Ricardo Salmon, Pascal Poupart
ID: 410

Almost Matching Exactly With Instrumental Variables

M.Usaid Awan, Yameng Liu, Marco Morucci, Sudeepa Roy, Cynthia Rudin, Alexander Volfovsky
ID: 411

Low Frequency Adversarial Perturbation

Chuan Guo, Jared S. Frank, Kilian Q. Weinberger
ID: 427

Markov Logic Networks for Knowledge Base Completion: A Theoretical Analysis Under the MCAR Assumption

Ondrej Kuzelka, Jesse Davis
ID: 428

Identification In Missing Data Models Represented By Directed Acyclic Graphs

Rohit Bhattacharya, Razieh Nabi, James M. Robins, Ilya Shpitser
ID: 432

A Weighted Mini-Bucket Bound for Solving Influence Diagram

Junkyu Lee, Radu Marinescu, Rina Dechter
ID: 435

Subspace Inference for Bayesian Deep Learning

Wesley Maddox, Pavel Izmailov, Polina Kirichenko, Timur Garipov, Dmitry Vetrov, Andrew Gordon Wilson
ID: 440

Off-Policy Policy Gradient with Stationary Distribution Correction

Yao Liu, Adith Swaminathan, Alekh Agarwal, Emma Brunskill
ID: 441

Co-Training for Policy Learning

Jialin Song, Ravi Lanka, Yisong Yue, Masahiro Ono
ID: 443

Variational Inference of Penalized Regression with Submodular Functions

Koh Takeuchi, Yuichi Yoshida, Yoshinobu Kawahara
ID: 450

Probability Distillation: A Caveat and Alternatives

Chin-Wei Huang, Faruk Ahmed, Kundan Kumar, Alexandre Lacoste, Aaron Courville
ID: 468

Bayesian Optimization with Binary Auxiliary Information

Yehong Zhang, Zhongxiang Dai, Bryan Kian Hsiang Low
ID: 481

On Open-Universe Causal Reasoning

Duligur Ibeling, Thomas Icard
ID: 496

Embarrassingly Parallel MCMC Using Deep Invertible Transformations

Diego Mesquita, Paul Blomstedt, Samuel Kaski
ID: 508

Fast Proximal Gradient Descent for Non-convex Optimization

Yingzhen Yang, Jiahui Yu
ID: 511

Block Neural Autoregressive Flow

Nicola De Cao, Wilker Aziz, Ivan Titov
ID: 512

Exclusivity Graph Approach to Instrumental Inequalities

Davide Poderini, Rafael Chaves, Iris Agresti, Gonzalo Carvacho, Fabio Sciarrino

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