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Volume 124: Conference on Uncertainty in Artificial Intelligence, 3-6 August 2020, Virtual

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Editors: Jonas Peters, David Sontag

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Semi-supervised learning, causality, and the conditional cluster assumption

Julius Kügelgen, Alexander Mey, Marco Loog, Bernhard Schölkopf; PMLR 124:1-10

Finite-sample Analysis of Greedy-GQ with Linear Function Approximation under Markovian Noise

Yue Wang, Shaofeng Zou; PMLR 124:11-20

PAC-Bayesian Contrastive Unsupervised Representation Learning

Kento Nozawa, Pascal Germain, Benjamin Guedj; PMLR 124:21-30

Static and Dynamic Values of Computation in MCTS

Eren Sezener, Peter Dayan; PMLR 124:31-40

Kernel Conditional Moment Test via Maximum Moment Restriction

Krikamol Muandet, Wittawat Jitkrittum, Jonas Kübler; PMLR 124:41-50

Bounding the expected run-time of nonconvex optimization with early stopping

Thomas Flynn, Kwangmin Yu, Abid Malik, Nicholas D’Imperio, Shinjae Yoo; PMLR 124:51-60

Amortized variance reduction for doubly stochastic objective

Ayman Boustati, Sattar Vakili, James Hensman, ST John; PMLR 124:61-70

Randomized Exploration for Non-Stationary Stochastic Linear Bandits

Baekjin Kim, Ambuj Tewari; PMLR 124:71-80

Divergence-Based Motivation for Online EM and Combining Hidden Variable Models

Ehsan Amid, Manfred K. Warmuth; PMLR 124:81-90

Iterative Channel Estimation for Discrete Denoising under Channel Uncertainty

Hongjoon Ahn, Taesup Moon; PMLR 124:91-100

Nonparametric Fisher Geometry with Application to Density Estimation

Andrew Holbrook, Shiwei Lan, Jeffrey Streets, Babak Shahbaba; PMLR 124:101-110

Learning Intrinsic Rewards as a Bi-Level Optimization Problem

Bradly Stadie, Lunjun Zhang, Jimmy Ba; PMLR 124:111-120

Regret Bounds for Decentralized Learning in Cooperative Multi-Agent Dynamical Systems

Seyed Mohammad Asghari, Yi Ouyang, Ashutosh Nayyar; PMLR 124:121-130

Learning Behaviors with Uncertain Human Feedback

Xu He, Haipeng Chen, Bo An; PMLR 124:131-140

Regret Analysis of Bandit Problems with Causal Background Knowledge

Yangyi Lu, Amirhossein Meisami, Ambuj Tewari, William Yan; PMLR 124:141-150

Evaluation of Causal Structure Learning Algorithms via Risk Estimation

Marco Eigenmann, Sach Mukherjee, Marloes Maathuis; PMLR 124:151-160

Kidney Exchange with Inhomogeneous Edge Existence Uncertainty

hoda bidkhori, John Dickerson, Duncan McElfresh, Ke Ren; PMLR 124:161-170

On the design of consequential ranking algorithms

Behzad Tabibian, Vicenç Gómez, Abir De, Bernhard Schölkopf, Manuel Gomez Rodriguez; PMLR 124:171-180

Fair Contextual Multi-Armed Bandits: Theory and Experiments

Yifang Chen, Alex Cuellar, Haipeng Luo, Jignesh Modi, Heramb Nemlekar, Stefanos Nikolaidis; PMLR 124:181-190

Submodular Bandit Problem Under Multiple Constraints

Sho Takemori, Masahiro Sato, Takashi Sonoda, Janmajay Singh, Tomoko Ohkuma; PMLR 124:191-200

Exploration Analysis in Finite-Horizon Turn-based Stochastic Games

Jialian Li, Yichi Zhou, Tongzheng Ren, Jun Zhu; PMLR 124:201-210

Amortized Nesterov’s Momentum: A Robust Momentum and Its Application to Deep Learning

Kaiwen Zhou, Yanghua Jin, Qinghua Ding, James Cheng; PMLR 124:211-220

Testing Goodness of Fit of Conditional Density Models with Kernels

Wittawat Jitkrittum, Heishiro Kanagawa, Bernhard Schölkopf; PMLR 124:221-230

Scalable and Flexible Clustering of Grouped Data via Parallel and Distributed Sampling in Versatile Hierarchical Dirichlet Processes

Or Dinari, Oren Freifeld; PMLR 124:231-240

Statistically Efficient Greedy Equivalence Search

Max Chickering; PMLR 124:241-249

Robust Collective Classification against Structural Attacks

Kai Zhou, Yevgeniy Vorobeychik; PMLR 124:250-259

Efficient Rollout Strategies for Bayesian Optimization

Eric Lee, David Eriksson, David Bindel, Bolong Cheng, Mike Mccourt; PMLR 124:260-269

IDA with Background Knowledge

Zhuangyan Fang, Yangbo He; PMLR 124:270-279

Complete Dictionary Learning via $\ell_p$-norm Maximization

Yifei Shen, Ye Xue, Jun Zhang, Khaled Letaief, Vincent Lau; PMLR 124:280-289

Collapsible IDA: Collapsing Parental Sets for Locally Estimating Possible Causal Effects

Yue Liu, Zhuangyan Fang, Yangbo He, Zhi Geng; PMLR 124:290-299

Learning Joint Nonlinear Effects from Single-variable Interventions in the Presence of Hidden Confounders

Sorawit Saengkyongam, Ricardo Silva; PMLR 124:300-309

Causal screening in dynamical systems

Søren Wengel Mogensen; PMLR 124:310-319

Bayesian Online Prediction of Change Points

Diego Agudelo-España, Sebastian Gomez-Gonzalez, Stefan Bauer, Bernhard Schölkopf, Jan Peters; PMLR 124:320-329

Walking on Two Legs: Learning Image Segmentation with Noisy Labels

Guohua Cheng, Hongli Ji, Yan Tian; PMLR 124:330-339

Election Control by Manipulating Issue Significance

Andrew Estornell, Sanmay Das, Edith Elkind, Yevgeniy Vorobeychik; PMLR 124:340-349

Coresets for Estimating Means and Mean Square Error with Limited Greedy Samples

Saeed Vahidian, Baharan Mirzasoleiman, Alexander Cloninger; PMLR 124:350-359

Robust Spatial-Temporal Incident Prediction

Ayan Mukhopadhyay, Kai Wang, Andrew Perrault, Mykel Kochenderfer, Milind Tambe, Yevgeniy Vorobeychik; PMLR 124:360-369

Lagrangian Decomposition for Neural Network Verification

Rudy Bunel, Alessandro De Palma, Alban Desmaison, Krishnamurthy Dvijotham, Pushmeet Kohli, Philip Torr, M. Pawan Kumar; PMLR 124:370-379

Robust modal regression with direct gradient approximation of modal regression risk

Hiroaki Sasaki, Tomoya Sakai, Takafumi Kanamori; PMLR 124:380-389

A Simple Online Algorithm for Competing with Dynamic Comparators

Yu-Jie Zhang, Peng Zhao, Zhi-Hua Zhou; PMLR 124:390-399

Skewness Ranking Optimization for Personalized Recommendation

Yu-Neng Chuang, Chih-Ming Chen, Chuan-Ju Wang, Ming-Feng Tsai; PMLR 124:400-409

High Dimensional Discrete Integration over the Hypergrid

Raj Kumar Maity, Arya Mazumdar, Soumyabrata Pal; PMLR 124:410-419

Neural Likelihoods via Cumulative Distribution Functions

Pawel Chilinski, Ricardo Silva; PMLR 124:420-429

Unknown mixing times in apprenticeship and reinforcement learning

Tom Zahavy, Alon Cohen, Haim Kaplan, Yishay Mansour; PMLR 124:430-439

TX-Ray: Quantifying and Explaining Model-Knowledge Transfer in (Un-)Supervised NLP

Nils Rethmeier, Vageesh Kumar Saxena, Isabelle Augenstein; PMLR 124:440-449

What You See May Not Be What You Get: UCB Bandit Algorithms Robust to $\varepsilon$-Contamination

Laura Niss, Ambuj Tewari; PMLR 124:450-459

The Hawkes Edge Partition Model for Continuous-time Event-based Temporal Networks

Sikun Yang, Heinz Koeppl; PMLR 124:460-469

Learning by Repetition: Stochastic Multi-armed Bandits under Priming Effect

Priyank Agrawal, Theja Tulabandula; PMLR 124:470-479

Compositional uncertainty in deep Gaussian processes

Ivan Ustyuzhaninov, Ieva Kazlauskaite, Markus Kaiser, Erik Bodin, Neill Campbell, Carl Henrik Ek; PMLR 124:480-489

Streaming Nonlinear Bayesian Tensor Decomposition

Zhimeng Pan, Zheng Wang, Shandian Zhe; PMLR 124:490-499

Relaxed Multivariate Bernoulli Distribution and Its Applications to Deep Generative Models

Xi Wang, Junming Yin; PMLR 124:500-509

One-Bit Compressed Sensing via One-Shot Hard Thresholding

Jie Shen; PMLR 124:510-519

GPIRT: A Gaussian Process Model for Item Response Theory

JBrandon Duck-Mayr, Roman Garnett, Jacob Montgomery; PMLR 124:520-529

Identifying causal effects in maximally oriented partially directed acyclic graphs

Emilija Perkovic; PMLR 124:530-539

Pairwise Supervised Hashing with Bernoulli Variational Auto-Encoder and Self-Control Gradient Estimator

Siamak Zamani Dadaneh, Shahin Boluki, Mingzhang Yin, Mingyuan Zhou, Xiaoning Qian; PMLR 124:540-549

Q* Approximation Schemes for Batch Reinforcement Learning: A Theoretical Comparison

Tengyang Xie, Nan Jiang; PMLR 124:550-559

Towards Threshold Invariant Fair Classification

Mingliang Chen, Min Wu; PMLR 124:560-569

Optimal Statistical Hypothesis Testing for Social Choice

Lirong Xia; PMLR 124:570-579

A SUPER* Algorithm to Optimize Paper Bidding in Peer Review

Tanner Fiez, Nihar Shah, Lillian Ratliff; PMLR 124:580-589

Measurement Dependence Inducing Latent Causal Models

Alex Markham, Moritz Grosse-Wentrup; PMLR 124:590-599

The Indian Chefs Process

Patrick Dallaire, Luca Ambrogioni, Ludovic Trottier, Umut Güçlü, Max Hinne, Philippe Giguère, Marcel Gerven, François Laviolette; PMLR 124:600-608

Spectral Methods for Ranking with Scarce Data

Lalit Jain, Anna Gilbert, Umang Varma; PMLR 124:609-618

Anchored Causal Inference in the Presence of Measurement Error

Basil Saeed, Anastasiya Belyaeva, Yuhao Wang, Caroline Uhler; PMLR 124:619-628

How Private Are Commonly-Used Voting Rules?

Ao LIU, Yun Lu, Lirong Xia, Vassilis Zikas; PMLR 124:629-638

Differentially Private Small Dataset Release Using Random Projections

Lovedeep Gondara, Ke Wang; PMLR 124:639-648

Semi-supervised Sequential Generative Models

Michael Teng, Tuan Anh Le, Adam Scibior, Frank Wood; PMLR 124:649-658

Robust contrastive learning and nonlinear ICA in the presence of outliers

Hiroaki Sasaki, Takashi Takenouchi, Ricardo Monti, Aapo Hyvarinen; PMLR 124:659-668

Selling Data at an Auction under Privacy Constraints

Mengxiao Zhang, Fernando Beltran, Jiamou Liu; PMLR 124:669-678

Mixed-Membership Stochastic Block Models for Weighted Networks

Adrien Dulac, Eric Gaussier, Christine Largeron; PMLR 124:679-688

MaskAAE: Latent space optimization for Adversarial Auto-Encoders

Arnab Mondal, Sankalan Pal Chowdhury, Aravind Jayendran, Himanshu Asnani, Parag Singla, Prathosh A P; PMLR 124:689-698

Slice Sampling for General Completely Random Measures

Peiyuan Zhu, Alexandre Bouchard-Cote, Trevor Campbell; PMLR 124:699-708

Semi-Supervised Learning: the Case When Unlabeled Data is Equally Useful

Jingge Zhu; PMLR 124:709-718

Generalized Bayesian Posterior Expectation Distillation for Deep Neural Networks

Meet Vadera, Brian Jalaian, Benjamin Marlin; PMLR 124:719-728

Complex Markov Logic Networks: Expressivity and Liftability

Ondrej Kuzelka; PMLR 124:729-738

Faster algorithms for Markov equivalence

Zhongyi Hu, Robin Evans; PMLR 124:739-748

Verifying Individual Fairness in Machine Learning Models

Philips George John, Deepak Vijaykeerthy, Diptikalyan Saha; PMLR 124:749-758

An Interpretable and Sample Efficient Deep Kernel for Gaussian Process

Yijue Dai, Tianjian Zhang, Zhidi Lin, Feng Yin, Sergios Theodoridis, Shuguang Cui; PMLR 124:759-768

Amortized Bayesian Optimization over Discrete Spaces

Kevin Swersky, Yulia Rubanova, David Dohan, Kevin Murphy; PMLR 124:769-778

Batch simulations and uncertainty quantification in Gaussian process surrogate approximate Bayesian computation

Marko Jarvenpaa, Aki Vehtari, Pekka Marttinen; PMLR 124:779-788

Deep Sigma Point Processes

Martin Jankowiak, Geoff Pleiss, Jacob Gardner; PMLR 124:789-798

Robust $k$-means++

Amit Deshpande, Praneeth Kacham, Rameshwar Pratap; PMLR 124:799-808

On Counterfactual Explanations under Predictive Multiplicity

Martin Pawelczyk, Klaus Broelemann, Gjergji. Kasneci; PMLR 124:809-818

A Practical Riemannian Algorithm for Computing Dominant Generalized Eigenspace

Zhiqiang Xu, Ping Li; PMLR 124:819-828

No-regret Exploration in Contextual Reinforcement Learning

Aditya Modi, Ambuj Tewari; PMLR 124:829-838

Layering-MCMC for Structure Learning in Bayesian Networks

Jussi Viinikka, Mikko Koivisto; PMLR 124:839-848

C-MI-GAN : Estimation of Conditional Mutual Information using MinMax formulation

Arnab Mondal, Arnab Bhattacharjee, Sudipto Mukherjee, Himanshu Asnani, Sreeram Kannan, Prathosh A P; PMLR 124:849-858

Stochastic Variational Inference for Dynamic Correlated Topic Models

Federico Tomasi, Praveen Chandar, Gal Levy-Fix, Mounia Lalmas-Roelleke, Zhenwen Dai; PMLR 124:859-868

Adversarial Learning for 3D Matching

Wei Xing, Brian Ziebart; PMLR 124:869-878

Ordering Variables for Weighted Model Integration

Vincent Derkinderen, Evert Heylen, Pedro Zuidberg Dos Martires, Samuel Kolb, Luc Raedt; PMLR 124:879-888

Online Parameter-Free Learning of Multiple Low Variance Tasks

Giulia Denevi, Massimiliano Pontil, Dimitrios Stamos; PMLR 124:889-898

Zeroth Order Non-convex optimization with Dueling-Choice Bandits

Yichong Xu, Aparna Joshi, Aarti Singh, Artur Dubrawski; PMLR 124:899-908

Semi-bandit Optimization in the Dispersed Setting

Travis Dick, Wesley Pegden, Maria-Florina Balcan; PMLR 124:909-918

Adapting Text Embeddings for Causal Inference

Victor Veitch, Dhanya Sridhar, David Blei; PMLR 124:919-928

Joint Stochastic Approximation and Its Application to Learning Discrete Latent Variable Models

Zhijian Ou, Yunfu Song; PMLR 124:929-938

Hidden Markov Nonlinear ICA: Unsupervised Learning from Nonstationary Time Series

Hermanni Hälvä, Aapo Hyvarinen; PMLR 124:939-948

Identification and Estimation of Causal Effects Defined by Shift Interventions

Numair Sani, Jaron Lee, Ilya Shpitser; PMLR 124:949-958

Risk Bounds for Low Cost Bipartite Ranking

San Gultekin, John Paisley; PMLR 124:959-968

Multitask Soft Option Learning

Maximilian Igl, Andrew Gambardella, Jinke He, Nantas Nardelli, N Siddharth, Wendelin Boehmer, Shimon Whiteson; PMLR 124:969-978

99% of Worker-Master Communication in Distributed Optimization Is Not Needed

Konstantin Mishchenko, Filip Hanzely, Peter Richtarik; PMLR 124:979-988

Graphical continuous Lyapunov models

Gherardo Varando, Niels Richard Hansen; PMLR 124:989-998

Structure Learning for Cyclic Linear Causal Models

Carlos Amendola, Philipp Dettling, Mathias Drton, Federica Onori, Jun Wu; PMLR 124:999-1008

Sensor Placement for Spatial Gaussian Processes with Integral Observations

Krista Longi, Chang Rajani, Tom Sillanpää, Joni Mäkinen, Timo Rauhala, Ari Salmi, Edward Haeggström, Arto Klami; PMLR 124:1009-1018

Active Model Estimation in Markov Decision Processes

Jean Tarbouriech, Shubhanshu Shekhar, Matteo Pirotta, Mohammad Ghavamzadeh, Alessandro Lazaric; PMLR 124:1019-1028

Dueling Posterior Sampling for Preference-Based Reinforcement Learning

Ellen Novoseller, Yibing Wei, Yanan Sui, Yisong Yue, Joel Burdick; PMLR 124:1029-1038

Permutation-Based Causal Structure Learning with Unknown Intervention Targets

Chandler Squires, Yuhao Wang, Caroline Uhler; PMLR 124:1039-1048

MASSIVE: Tractable and Robust Bayesian Learning of Many-Dimensional Instrumental Variable Models

Ioan Gabriel Bucur, Tom Claassen, Tom Heskes; PMLR 124:1049-1058

Popularity Agnostic Evaluation of Knowledge Graph Embeddings

Aisha Mohamed, Shameem Parambath, Zoi Kaoudi, Ashraf Aboulnaga; PMLR 124:1059-1068

Learning LWF Chain Graphs: A Markov Blanket Discovery Approach

Mohammad Ali Javidian, Marco Valtorta, Pooyan Jamshidi; PMLR 124:1069-1078

Batch norm with entropic regularization turns deterministic autoencoders into generative models

Amur Ghose, Abdullah Rashwan, Pascal Poupart; PMLR 124:1079-1088

Adaptive Hyper-box Matching for Interpretable Individualized Treatment Effect Estimation

Marco Morucci, Vittorio Orlandi, Sudeepa Roy, Cynthia Rudin, Alexander Volfovsky; PMLR 124:1089-1098

Generalized Policy Elimination: an efficient algorithm for Nonparametric Contextual Bandits

Aurelien Bibaut, Antoine Chambaz, Mark Laan; PMLR 124:1099-1108

Differentially Private Top-k Selection via Stability on Unknown Domain

Ricardo Silva Carvalho, Ke Wang, Lovedeep Gondara, Chunyan Miao; PMLR 124:1109-1118

Active Learning of Conditional Mean Embeddings via Bayesian Optimisation

Sayak Ray Chowdhury, Rafael Oliveira, Fabio Ramos; PMLR 124:1119-1128

Flexible Prior Elicitation via the Prior Predictive Distribution

Marcelo Hartmann, Georgi Agiashvili, Paul Bürkner, Arto Klami; PMLR 124:1129-1138

Model-Augmented Conditional Mutual Information Estimation for Feature Selection

Alan Yang, AmirEmad Ghassami, Maxim Raginsky, Negar Kiyavash, Elyse Rosenbaum; PMLR 124:1139-1148

Finite-Memory Near-Optimal Learning for Markov Decision Processes with Long-Run Average Reward

Jan Kretinsky, Fabian Michel, Lukas Michel, Guillermo Perez; PMLR 124:1149-1158

Constraint-Based Causal Discovery using Partial Ancestral Graphs in the presence of Cycles

Joris M. Mooij, Tom Claassen; PMLR 124:1159-1168

Estimation Rates for Sparse Linear Cyclic Causal Models

Jan-Christian Huetter, Philippe Rigollet; PMLR 124:1169-1178

Prediction Intervals: Split Normal Mixture from Quality-Driven Deep Ensembles

Tárik S. Salem, Helge Langseth, Heri Ramampiaro; PMLR 124:1179-1187

On the Relationship Between Probabilistic Circuits and Determinantal Point Processes

Honghua Zhang, Steven Holtzen, Guy Broeck; PMLR 124:1188-1197

Probabilistic Safety for Bayesian Neural Networks

Matthew Wicker, Luca Laurenti, Andrea Patane, Marta Kwiatkowska; PMLR 124:1198-1207

Distortion estimates for approximate Bayesian inference

Hanwen Xing, Geoff Nicholls, Jeong (Kate) Lee; PMLR 124:1208-1217

Mutual Information Based Knowledge Transfer Under State-Action Dimension Mismatch

Michael Wan, Tanmay Gangwani, Jian Peng; PMLR 124:1218-1227

Provably Efficient Third-Person Imitation from Offline Observation

Aaron Zweig, Joan Bruna; PMLR 124:1228-1237

Automated Dependence Plots

David Inouye, Liu Leqi, Joon Sik Kim, Bryon Aragam, Pradeep Ravikumar; PMLR 124:1238-1247

EiGLasso: Scalable Estimation of Cartesian Product of Sparse Inverse Covariance Matrices

Jun Ho Yoon, Seyoung Kim; PMLR 124:1248-1257

Improved Vector Pruning in Exact Algorithms for Solving POMDPs

Eric Hansen, Thomas Bowman; PMLR 124:1258-1267

Symbolic Querying of Vector Spaces: Probabilistic Databases Meets Relational Embeddings

Tal Friedman, Guy Broeck; PMLR 124:1268-1277

Learning to learn generative programs with Memoised Wake-Sleep

Luke Hewitt, Tuan Anh Le, Joshua Tenenbaum; PMLR 124:1278-1287

Flexible Approximate Inference via Stratified Normalizing Flows

Chris Cundy, Stefano Ermon; PMLR 124:1288-1297

Bounded Rationality in Las Vegas: Probabilistic Finite Automata Play Multi-Armed Bandits

Xinming Liu, Joseph Halpern; PMLR 124:1298-1307

Greedy Policy Search: A Simple Baseline for Learnable Test-Time Augmentation

Alexander Lyzhov, Yuliya Molchanova, Arsenii Ashukha, Dmitry Molchanov, Dmitry Vetrov; PMLR 124:1308-1317

Non Parametric Graph Learning for Bayesian Graph Neural Networks

Soumyasundar Pal, Saber Malekmohammadi, Florence Regol, Yingxue Zhang, Yishi Xu, Mark Coates; PMLR 124:1318-1327

Stable Policy Optimization via Off-Policy Divergence Regularization

Ahmed Touati, Amy Zhang, Joelle Pineau, Pascal Vincent; PMLR 124:1328-1337

PoRB-Nets: Poisson Process Radial Basis Function Networks

Beau Coker, Melanie Fernandez Pradier, Finale Doshi-Velez; PMLR 124:1338-1347

Deriving Bounds And Inequality Constraints Using Logical Relations Among Counterfactuals

Noam Finkelstein, Ilya Shpitser; PMLR 124:1348-1357

Locally Masked Convolution for Autoregressive Models

Ajay Jain, Pieter Abbeel, Deepak Pathak; PMLR 124:1358-1367

Time Series Analysis using a Kernel based Multi-Modal Uncertainty Decomposition Framework

Rishabh Singh, Jose Principe; PMLR 124:1368-1377

OCEAN: Online Task Inference for Compositional Tasks with Context Adaptation

Hongyu Ren, Yuke Zhu, Jure Leskovec, Animashree Anandkumar, Animesh Garg; PMLR 124:1378-1387

Discovering contemporaneous and lagged causal relations in autocorrelated nonlinear time series datasets

Jakob Runge; PMLR 124:1388-1397

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