UAI 2020

140 papers

A Simple Online Algorithm for Competing with Dynamic Comparators

Yu-Jie Zhang, Peng Zhao, Zhi-Hua Zhou

Robust modal regression with direct gradient approximation of modal regression risk

Hiroaki Sasaki, Tomoya Sakai, Takafumi Kanamori

Lagrangian Decomposition for Neural Network Verification

Rudy Bunel, Alessandro De Palma, Alban Desmaison, Krishnamurthy Dvijotham, Pushmeet Kohli

Robust Spatial-Temporal Incident Prediction

Ayan Mukhopadhyay, Kai Wang, Andrew Perrault, Mykel Kochenderfer, Milind Tambe

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

Saeed Vahidian, Baharan Mirzasoleiman, Alexander Cloninger

Election Control by Manipulating Issue Significance

Andrew Estornell, Sanmay Das, Edith Elkind, Yevgeniy Vorobeychik

Walking on Two Legs: Learning Image Segmentation with Noisy Labels

Guohua Cheng, Hongli Ji, Yan Tian

Bayesian Online Prediction of Change Points

Diego Agudelo-España, Sebastian Gomez-Gonzalez, Stefan Bauer, Bernhard Schölkopf, Jan Peters

Causal screening in dynamical systems

Søren Wengel Mogensen

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

Sorawit Saengkyongam, Ricardo Silva

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

Yue Liu, Zhuangyan Fang, Yangbo He, Zhi Geng

Complete Dictionary Learning via ℓ_p-norm Maximization

Yifei Shen, Ye XUE, Jun Zhang, Khaled Letaief, Vincent Lau

IDA with Background Knowledge

Zhuangyan Fang, Yangbo He

Efficient Rollout Strategies for Bayesian Optimization

Eric Lee, David Eriksson, David Bindel, Bolong Cheng, Mike Mccourt

Robust Collective Classification against Structural Attacks

Kai Zhou, Yevgeniy Vorobeychik

Statistically Efficient Greedy Equivalence Search

Max Chickering

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

Or Dinari, Oren Freifeld

Testing Goodness of Fit of Conditional Density Models with Kernels

Wittawat Jitkrittum, Heishiro Kanagawa, Bernhard Schölkopf

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

Kaiwen Zhou, Yanghua Jin, Qinghua Ding, James Cheng

Exploration Analysis in Finite-Horizon Turn-based Stochastic Games

Jialian Li, Yichi Zhou, Tongzheng Ren, Jun Zhu

Submodular Bandit Problem Under Multiple Constraints

Sho Takemori, Masahiro Sato, Takashi Sonoda, Janmajay Singh, Tomoko Ohkuma

Fair Contextual Multi-Armed Bandits: Theory and Experiments

Yifang Chen, Alex Cuellar, Haipeng Luo, Jignesh Modi, Heramb Nemlekar

On the design of consequential ranking algorithms

Behzad Tabibian, Vicenç Gómez, Abir De, Bernhard Schölkopf, Manuel Gomez Rodriguez

Kidney Exchange with Inhomogeneous Edge Existence Uncertainty

Hoda Bidkhori, John Dickerson, Duncan McElfresh, Ke Ren

Evaluation of Causal Structure Learning Algorithms via Risk Estimation

Marco Eigenmann, Sach Mukherjee, Marloes Maathuis

Regret Analysis of Bandit Problems with Causal Background Knowledge

Yangyi Lu, Amirhossein Meisami, Ambuj Tewari, William Yan

Learning Behaviors with Uncertain Human Feedback

Xu He, Haipeng Chen, Bo An

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

Seyed Mohammad Asghari, Yi Ouyang, Ashutosh Nayyar

Learning Intrinsic Rewards as a Bi-Level Optimization Problem

Bradly Stadie, Lunjun Zhang, Jimmy Ba

Nonparametric Fisher Geometry with Application to Density Estimation

Andrew Holbrook, Shiwei Lan, Jeffrey Streets, Babak Shahbaba

Iterative Channel Estimation for Discrete Denoising under Channel Uncertainty

Hongjoon Ahn, Taesup Moon

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

Ehsan Amid, Manfred K. Warmuth

Randomized Exploration for Non-Stationary Stochastic Linear Bandits

Baekjin Kim, Ambuj Tewari

Amortized variance reduction for doubly stochastic objective

Ayman Boustati, Sattar Vakili, James Hensman, ST John

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

Thomas Flynn, Kwangmin Yu, Abid Malik, Nicholas D’Imperio, Shinjae Yoo

Kernel Conditional Moment Test via Maximum Moment Restriction

Krikamol Muandet, Wittawat Jitkrittum, Jonas Kübler

Static and Dynamic Values of Computation in MCTS

Eren Sezener, Peter Dayan

PAC-Bayesian Contrastive Unsupervised Representation Learning

Kento Nozawa, Pascal Germain, Benjamin Guedj

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

Yue Wang, Shaofeng Zou

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

Julius Kügelgen, Alexander Mey, Marco Loog, Bernhard Schölkopf