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Proceedings of Machine Learning Research

Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research
Proceedings of Machine Learning Research
PMLR · 2026-06-02 · via Proceedings of Machine Learning Research

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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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Filter Authors: Filter Titles:

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

; Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence (UAI), PMLR 124:1-10

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

Yue Wang, Shaofeng Zou; Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence (UAI), PMLR 124:11-20

[abs][Download PDF][Supplementary PDF]

PAC-Bayesian Contrastive Unsupervised Representation Learning

Kento Nozawa, Pascal Germain, Benjamin Guedj; Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence (UAI), PMLR 124:21-30

[abs][Download PDF][Supplementary PDF]

Static and Dynamic Values of Computation in MCTS

Eren Sezener, Peter Dayan; Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence (UAI), PMLR 124:31-40

[abs][Download PDF][Supplementary PDF]

Kernel Conditional Moment Test via Maximum Moment Restriction

Krikamol Muandet, Wittawat Jitkrittum, Jonas Kübler; Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence (UAI), PMLR 124:41-50

[abs][Download PDF][Supplementary PDF]

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

Thomas Flynn, Kwangmin Yu, Abid Malik, Nicholas D’Imperio, Shinjae Yoo; Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence (UAI), PMLR 124:51-60

[abs][Download PDF][Supplementary PDF]

Amortized variance reduction for doubly stochastic objective

Ayman Boustati, Sattar Vakili, James Hensman, ST John; Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence (UAI), PMLR 124:61-70

[abs][Download PDF][Supplementary PDF]

Randomized Exploration for Non-Stationary Stochastic Linear Bandits

Baekjin Kim, Ambuj Tewari; Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence (UAI), PMLR 124:71-80

[abs][Download PDF][Supplementary PDF]

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

Ehsan Amid, Manfred K. Warmuth; Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence (UAI), PMLR 124:81-90

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Iterative Channel Estimation for Discrete Denoising under Channel Uncertainty

Hongjoon Ahn, Taesup Moon; Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence (UAI), PMLR 124:91-100

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Nonparametric Fisher Geometry with Application to Density Estimation

Andrew Holbrook, Shiwei Lan, Jeffrey Streets, Babak Shahbaba; Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence (UAI), PMLR 124:101-110

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Learning Intrinsic Rewards as a Bi-Level Optimization Problem

Bradly Stadie, Lunjun Zhang, Jimmy Ba; Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence (UAI), PMLR 124:111-120

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

Seyed Mohammad Asghari, Yi Ouyang, Ashutosh Nayyar; Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence (UAI), PMLR 124:121-130

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Learning Behaviors with Uncertain Human Feedback

Xu He, Haipeng Chen, Bo An; Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence (UAI), PMLR 124:131-140

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Regret Analysis of Bandit Problems with Causal Background Knowledge

Yangyi Lu, Amirhossein Meisami, Ambuj Tewari, William Yan; Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence (UAI), PMLR 124:141-150

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Evaluation of Causal Structure Learning Algorithms via Risk Estimation

Marco Eigenmann, Sach Mukherjee, Marloes Maathuis; Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence (UAI), PMLR 124:151-160

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Kidney Exchange with Inhomogeneous Edge Existence Uncertainty

hoda bidkhori, John Dickerson, Duncan McElfresh, Ke Ren; Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence (UAI), PMLR 124:161-170

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On the design of consequential ranking algorithms

Behzad Tabibian, Vicenç Gómez, Abir De, Bernhard Schölkopf, Manuel Gomez Rodriguez; Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence (UAI), PMLR 124:171-180

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Fair Contextual Multi-Armed Bandits: Theory and Experiments

Yifang Chen, Alex Cuellar, Haipeng Luo, Jignesh Modi, Heramb Nemlekar, Stefanos Nikolaidis; Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence (UAI), PMLR 124:181-190

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Submodular Bandit Problem Under Multiple Constraints

Sho Takemori, Masahiro Sato, Takashi Sonoda, Janmajay Singh, Tomoko Ohkuma; Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence (UAI), PMLR 124:191-200

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Exploration Analysis in Finite-Horizon Turn-based Stochastic Games

Jialian Li, Yichi Zhou, Tongzheng Ren, Jun Zhu; Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence (UAI), PMLR 124:201-210

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

Kaiwen Zhou, Yanghua Jin, Qinghua Ding, James Cheng; Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence (UAI), PMLR 124:211-220

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Testing Goodness of Fit of Conditional Density Models with Kernels

Wittawat Jitkrittum, Heishiro Kanagawa, Bernhard Schölkopf; Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence (UAI), PMLR 124:221-230

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

Or Dinari, Oren Freifeld; Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence (UAI), PMLR 124:231-240

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Statistically Efficient Greedy Equivalence Search

Max Chickering; Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence (UAI), PMLR 124:241-249

[abs][Download PDF][Supplementary PDF]

Robust Collective Classification against Structural Attacks

Kai Zhou, Yevgeniy Vorobeychik; Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence (UAI), PMLR 124:250-259

[abs][Download PDF][Supplementary PDF]

Efficient Rollout Strategies for Bayesian Optimization

Eric Lee, David Eriksson, David Bindel, Bolong Cheng, Mike Mccourt; Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence (UAI), PMLR 124:260-269

[abs][Download PDF][Supplementary PDF]

IDA with Background Knowledge

Zhuangyan Fang, Yangbo He; Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence (UAI), PMLR 124:270-279

[abs][Download PDF][Supplementary PDF]

Complete Dictionary Learning via $\ell_p$-norm Maximization

Yifei Shen, Ye Xue, Jun Zhang, Khaled Letaief, Vincent Lau; Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence (UAI), PMLR 124:280-289

[abs][Download PDF][Supplementary PDF]

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

Yue Liu, Zhuangyan Fang, Yangbo He, Zhi Geng; Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence (UAI), PMLR 124:290-299

[abs][Download PDF][Supplementary PDF]

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

Sorawit Saengkyongam, Ricardo Silva; Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence (UAI), PMLR 124:300-309

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Causal screening in dynamical systems

Søren Wengel Mogensen; Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence (UAI), PMLR 124:310-319

[abs][Download PDF][Supplementary PDF]

Bayesian Online Prediction of Change Points

Diego Agudelo-España, Sebastian Gomez-Gonzalez, Stefan Bauer, Bernhard Schölkopf, Jan Peters; Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence (UAI), PMLR 124:320-329

[abs][Download PDF][Supplementary PDF]

Walking on Two Legs: Learning Image Segmentation with Noisy Labels

Guohua Cheng, Hongli Ji, Yan Tian; Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence (UAI), PMLR 124:330-339

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Election Control by Manipulating Issue Significance

Andrew Estornell, Sanmay Das, Edith Elkind, Yevgeniy Vorobeychik; Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence (UAI), PMLR 124:340-349

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

Saeed Vahidian, Baharan Mirzasoleiman, Alexander Cloninger; Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence (UAI), PMLR 124:350-359

[abs][Download PDF][Supplementary PDF]

Robust Spatial-Temporal Incident Prediction

Ayan Mukhopadhyay, Kai Wang, Andrew Perrault, Mykel Kochenderfer, Milind Tambe, Yevgeniy Vorobeychik; Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence (UAI), PMLR 124:360-369

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Lagrangian Decomposition for Neural Network Verification

Rudy Bunel, Alessandro De Palma, Alban Desmaison, Krishnamurthy Dvijotham, Pushmeet Kohli, Philip Torr, M. Pawan Kumar; Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence (UAI), PMLR 124:370-379

[abs][Download PDF][Supplementary PDF]

Robust modal regression with direct gradient approximation of modal regression risk

Hiroaki Sasaki, Tomoya Sakai, Takafumi Kanamori; Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence (UAI), PMLR 124:380-389

[abs][Download PDF][Supplementary PDF]

A Simple Online Algorithm for Competing with Dynamic Comparators

Yu-Jie Zhang, Peng Zhao, Zhi-Hua Zhou; Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence (UAI), PMLR 124:390-399

[abs][Download PDF][Supplementary PDF]

Skewness Ranking Optimization for Personalized Recommendation

Chuan-Ju Wang, Yu-Neng Chuang, Chih-Ming Chen, Ming-Feng Tsai; Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence (UAI), PMLR 124:400-409

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High Dimensional Discrete Integration over the Hypergrid

Raj Kumar Maity, Arya Mazumdar, Soumyabrata Pal; Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence (UAI), PMLR 124:410-419

[abs][Download PDF][Supplementary PDF]

Neural Likelihoods via Cumulative Distribution Functions

Pawel Chilinski, Ricardo Silva; Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence (UAI), PMLR 124:420-429

[abs][Download PDF][Supplementary PDF]

Unknown mixing times in apprenticeship and reinforcement learning

Tom Zahavy, Alon Cohen, Haim Kaplan, Yishay Mansour; Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence (UAI), PMLR 124:430-439

[abs][Download PDF][Supplementary PDF]

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

Nils Rethmeier, Vageesh Kumar Saxena, Isabelle Augenstein; Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence (UAI), PMLR 124:440-449

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

Laura Niss, Ambuj Tewari; Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence (UAI), PMLR 124:450-459

[abs][Download PDF][Supplementary PDF]

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

Sikun Yang, Heinz Koeppl; Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence (UAI), PMLR 124:460-469

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

Priyank Agrawal, Theja Tulabandula; Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence (UAI), PMLR 124:470-479

[abs][Download PDF][Supplementary PDF]

Compositional uncertainty in deep Gaussian processes

Ivan Ustyuzhaninov, Ieva Kazlauskaite, Markus Kaiser, Erik Bodin, Neill Campbell, Carl Henrik Ek; Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence (UAI), PMLR 124:480-489

[abs][Download PDF][Supplementary PDF]

Streaming Nonlinear Bayesian Tensor Decomposition

Zhimeng Pan, Zheng Wang, Shandian Zhe; Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence (UAI), PMLR 124:490-499

[abs][Download PDF][Supplementary PDF]

Relaxed Multivariate Bernoulli Distribution and Its Applications to Deep Generative Models

Xi Wang, Junming Yin; Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence (UAI), PMLR 124:500-509

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One-Bit Compressed Sensing via One-Shot Hard Thresholding

Jie Shen; Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence (UAI), PMLR 124:510-519

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GPIRT: A Gaussian Process Model for Item Response Theory

JBrandon Duck-Mayr, Roman Garnett, Jacob Montgomery; Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence (UAI), PMLR 124:520-529

[abs][Download PDF][Supplementary PDF]

Identifying causal effects in maximally oriented partially directed acyclic graphs

Emilija Perkovic; Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence (UAI), PMLR 124:530-539

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

Siamak Zamani Dadaneh, Shahin Boluki, Mingzhang Yin, Mingyuan Zhou, Xiaoning Qian; Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence (UAI), PMLR 124:540-549

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

Tengyang Xie, Nan Jiang; Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence (UAI), PMLR 124:550-559

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Towards Threshold Invariant Fair Classification

Mingliang Chen, Min Wu; Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence (UAI), PMLR 124:560-569

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Optimal Statistical Hypothesis Testing for Social Choice

Lirong Xia; Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence (UAI), PMLR 124:570-579

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A SUPER* Algorithm to Optimize Paper Bidding in Peer Review

Tanner Fiez, Nihar Shah, Lillian Ratliff; Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence (UAI), PMLR 124:580-589

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Measurement Dependence Inducing Latent Causal Models

Alex Markham, Moritz Grosse-Wentrup; Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence (UAI), PMLR 124:590-599

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The Indian Chefs Process

Patrick Dallaire, Luca Ambrogioni, Ludovic Trottier, Umut Güçlü, Max Hinne, Philippe Giguère, Marcel Gerven, François Laviolette; Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence (UAI), PMLR 124:600-608

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Spectral Methods for Ranking with Scarce Data

Lalit Jain, Anna Gilbert, Umang Varma; Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence (UAI), PMLR 124:609-618

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Anchored Causal Inference in the Presence of Measurement Error

Basil Saeed, Anastasiya Belyaeva, Yuhao Wang, Caroline Uhler; Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence (UAI), PMLR 124:619-628

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How Private Are Commonly-Used Voting Rules?

Ao LIU, Yun Lu, Lirong Xia, Vassilis Zikas; Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence (UAI), PMLR 124:629-638

[abs][Download PDF][Supplementary PDF]

Differentially Private Small Dataset Release Using Random Projections

Lovedeep Gondara, Ke Wang; Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence (UAI), PMLR 124:639-648

[abs][Download PDF][Supplementary PDF]

Semi-supervised Sequential Generative Models

Michael Teng, Tuan Anh Le, Adam Scibior, Frank Wood; Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence (UAI), PMLR 124:649-658

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Robust contrastive learning and nonlinear ICA in the presence of outliers

Hiroaki Sasaki, Takashi Takenouchi, Ricardo Monti, Aapo Hyvarinen; Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence (UAI), PMLR 124:659-668

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Selling Data at an Auction under Privacy Constraints

Mengxiao Zhang, Fernando Beltran, Jiamou Liu; Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence (UAI), PMLR 124:669-678

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Mixed-Membership Stochastic Block Models for Weighted Networks

Adrien Dulac, Eric Gaussier, Christine Largeron; Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence (UAI), PMLR 124:679-688

[abs][Download PDF][Supplementary PDF]

MaskAAE: Latent space optimization for Adversarial Auto-Encoders

Arnab Mondal, Sankalan Pal Chowdhury, Aravind Jayendran, Himanshu Asnani, Parag Singla, Prathosh A P; Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence (UAI), PMLR 124:689-698

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Slice Sampling for General Completely Random Measures

Peiyuan Zhu, Alexandre Bouchard-Cote, Trevor Campbell; Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence (UAI), PMLR 124:699-708

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

Jingge Zhu; Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence (UAI), PMLR 124:709-718

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Generalized Bayesian Posterior Expectation Distillation for Deep Neural Networks

Meet Vadera, Brian Jalaian, Benjamin Marlin; Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence (UAI), PMLR 124:719-728

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Complex Markov Logic Networks: Expressivity and Liftability

Ondrej Kuzelka; Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence (UAI), PMLR 124:729-738

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Faster algorithms for Markov equivalence

Zhongyi Hu, Robin Evans; Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence (UAI), PMLR 124:739-748

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Verifying Individual Fairness in Machine Learning Models

Philips George John, Deepak Vijaykeerthy, Diptikalyan Saha; Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence (UAI), PMLR 124:749-758

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An Interpretable and Sample Efficient Deep Kernel for Gaussian Process

Yijue Dai, Tianjian Zhang, Zhidi Lin, Feng Yin, Sergios Theodoridis, Shuguang Cui; Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence (UAI), PMLR 124:759-768

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Amortized Bayesian Optimization over Discrete Spaces

Kevin Swersky, Yulia Rubanova, David Dohan, Kevin Murphy; Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence (UAI), PMLR 124:769-778

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

Marko Jarvenpaa, Aki Vehtari, Pekka Marttinen; Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence (UAI), PMLR 124:779-788

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Deep Sigma Point Processes

Martin Jankowiak, Geoff Pleiss, Jacob Gardner; Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence (UAI), PMLR 124:789-798

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Robust $k$-means++

Amit Deshpande, Praneeth Kacham, Rameshwar Pratap; Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence (UAI), PMLR 124:799-808

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On Counterfactual Explanations under Predictive Multiplicity

Martin Pawelczyk, Klaus Broelemann, Gjergji. Kasneci; Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence (UAI), PMLR 124:809-818

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A Practical Riemannian Algorithm for Computing Dominant Generalized Eigenspace

Zhiqiang Xu, Ping Li; Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence (UAI), PMLR 124:819-828

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No-regret Exploration in Contextual Reinforcement Learning

Aditya Modi, Ambuj Tewari; Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence (UAI), PMLR 124:829-838

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Layering-MCMC for Structure Learning in Bayesian Networks

Jussi Viinikka, Mikko Koivisto; Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence (UAI), PMLR 124:839-848

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

Arnab Mondal, Arnab Bhattacharjee, Sudipto Mukherjee, Himanshu Asnani, Sreeram Kannan, Prathosh A P; Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence (UAI), PMLR 124:849-858

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Stochastic Variational Inference for Dynamic Correlated Topic Models

Federico Tomasi, Praveen Chandar, Gal Levy-Fix, Mounia Lalmas-Roelleke, Zhenwen Dai; Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence (UAI), PMLR 124:859-868

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Adversarial Learning for 3D Matching

Wei Xing, Brian Ziebart; Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence (UAI), PMLR 124:869-878

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Ordering Variables for Weighted Model Integration

Vincent Derkinderen, Evert Heylen, Pedro Zuidberg Dos Martires, Samuel Kolb, Luc Raedt; Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence (UAI), PMLR 124:879-888

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Online Parameter-Free Learning of Multiple Low Variance Tasks

Giulia Denevi, Massimiliano Pontil, Dimitrios Stamos; Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence (UAI), PMLR 124:889-898

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Zeroth Order Non-convex optimization with Dueling-Choice Bandits

Yichong Xu, Aparna Joshi, Aarti Singh, Artur Dubrawski; Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence (UAI), PMLR 124:899-908

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Semi-bandit Optimization in the Dispersed Setting

Maria-Florina Balcan, Travis Dick, Wesley Pegden; Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence (UAI), PMLR 124:909-918

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Adapting Text Embeddings for Causal Inference

Victor Veitch, Dhanya Sridhar, David Blei; Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence (UAI), PMLR 124:919-928

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

Zhijian Ou, Yunfu Song; Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence (UAI), PMLR 124:929-938

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Hidden Markov Nonlinear ICA: Unsupervised Learning from Nonstationary Time Series

Hermanni Hälvä, Aapo Hyvarinen; Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence (UAI), PMLR 124:939-948

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Identification and Estimation of Causal Effects Defined by Shift Interventions

Numair Sani, Jaron Lee, Ilya Shpitser; Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence (UAI), PMLR 124:949-958

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Risk Bounds for Low Cost Bipartite Ranking

San Gultekin, John Paisley; Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence (UAI), PMLR 124:959-968

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Multitask Soft Option Learning

Maximilian Igl, Andrew Gambardella, Jinke He, Nantas Nardelli, N Siddharth, Wendelin Boehmer, Shimon Whiteson; Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence (UAI), PMLR 124:969-978

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

Konstantin Mishchenko, Filip Hanzely, Peter Richtarik; Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence (UAI), PMLR 124:979-988

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Graphical continuous Lyapunov models

Gherardo Varando, Niels Richard Hansen; Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence (UAI), PMLR 124:989-998

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Structure Learning for Cyclic Linear Causal Models

Carlos Amendola, Philipp Dettling, Mathias Drton, Federica Onori, Jun Wu; Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence (UAI), PMLR 124:999-1008

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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; Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence (UAI), PMLR 124:1009-1018

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Active Model Estimation in Markov Decision Processes

Jean Tarbouriech, Shubhanshu Shekhar, Matteo Pirotta, Mohammad Ghavamzadeh, Alessandro Lazaric; Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence (UAI), PMLR 124:1019-1028

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Dueling Posterior Sampling for Preference-Based Reinforcement Learning

Ellen Novoseller, Yibing Wei, Yanan Sui, Yisong Yue, Joel Burdick; Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence (UAI), PMLR 124:1029-1038

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Permutation-Based Causal Structure Learning with Unknown Intervention Targets

Chandler Squires, Yuhao Wang, Caroline Uhler; Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence (UAI), PMLR 124:1039-1048

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

Ioan Gabriel Bucur, Tom Claassen, Tom Heskes; Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence (UAI), PMLR 124:1049-1058

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Popularity Agnostic Evaluation of Knowledge Graph Embeddings

Aisha Mohamed, Shameem Parambath, Zoi Kaoudi, Ashraf Aboulnaga; Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence (UAI), PMLR 124:1059-1068

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Learning LWF Chain Graphs: A Markov Blanket Discovery Approach

Mohammad Ali Javidian, Marco Valtorta, Pooyan Jamshidi; Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence (UAI), PMLR 124:1069-1078

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Batch norm with entropic regularization turns deterministic autoencoders into generative models

Amur Ghose, Abdullah Rashwan, Pascal Poupart; Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence (UAI), PMLR 124:1079-1088

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Adaptive Hyper-box Matching for Interpretable Individualized Treatment Effect Estimation

Marco Morucci, Vittorio Orlandi, Sudeepa Roy, Cynthia Rudin, Alexander Volfovsky; Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence (UAI), PMLR 124:1089-1098

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Generalized Policy Elimination: an efficient algorithm for Nonparametric Contextual Bandits

Aurelien Bibaut, Antoine Chambaz, Mark Laan; Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence (UAI), PMLR 124:1099-1108

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Differentially Private Top-k Selection via Stability on Unknown Domain

Ricardo Silva Carvalho, Ke Wang, Lovedeep Gondara, Chunyan Miao; Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence (UAI), PMLR 124:1109-1118

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Active Learning of Conditional Mean Embeddings via Bayesian Optimisation

Sayak Ray Chowdhury, Rafael Oliveira, Fabio Ramos; Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence (UAI), PMLR 124:1119-1128

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Flexible Prior Elicitation via the Prior Predictive Distribution

Marcelo Hartmann, Georgi Agiashvili, Paul Bürkner, Arto Klami; Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence (UAI), PMLR 124:1129-1138

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Model-Augmented Conditional Mutual Information Estimation for Feature Selection

Alan Yang, AmirEmad Ghassami, Maxim Raginsky, Negar Kiyavash, Elyse Rosenbaum; Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence (UAI), PMLR 124:1139-1148

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

Jan Kretinsky, Fabian Michel, Lukas Michel, Guillermo Perez; Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence (UAI), PMLR 124:1149-1158

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

Joris M. Mooij, Tom Claassen; Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence (UAI), PMLR 124:1159-1168

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Estimation Rates for Sparse Linear Cyclic Causal Models

Jan-Christian Huetter, Philippe Rigollet; Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence (UAI), PMLR 124:1169-1178

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

Tárik S. Salem, Helge Langseth, Heri Ramampiaro; Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence (UAI), PMLR 124:1179-1187

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On the Relationship Between Probabilistic Circuits and Determinantal Point Processes

Honghua Zhang, Steven Holtzen, Guy Broeck; Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence (UAI), PMLR 124:1188-1197

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Probabilistic Safety for Bayesian Neural Networks

Matthew Wicker, Luca Laurenti, Andrea Patane, Marta Kwiatkowska; Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence (UAI), PMLR 124:1198-1207

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Distortion estimates for approximate Bayesian inference

Hanwen Xing, Geoff Nicholls, Jeong (Kate) Lee; Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence (UAI), PMLR 124:1208-1217

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Mutual Information Based Knowledge Transfer Under State-Action Dimension Mismatch

Michael Wan, Tanmay Gangwani, Jian Peng; Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence (UAI), PMLR 124:1218-1227

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Provably Efficient Third-Person Imitation from Offline Observation

Aaron Zweig, Joan Bruna; Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence (UAI), PMLR 124:1228-1237

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Automated Dependence Plots

David Inouye, Liu Leqi, Joon Sik Kim, Bryon Aragam, Pradeep Ravikumar; Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence (UAI), PMLR 124:1238-1247

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

Jun Ho Yoon, Seyoung Kim; Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence (UAI), PMLR 124:1248-1257

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Improved Vector Pruning in Exact Algorithms for Solving POMDPs

Eric Hansen, Thomas Bowman; Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence (UAI), PMLR 124:1258-1267

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Symbolic Querying of Vector Spaces: Probabilistic Databases Meets Relational Embeddings

Tal Friedman, Guy Broeck; Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence (UAI), PMLR 124:1268-1277

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Learning to learn generative programs with Memoised Wake-Sleep

Luke Hewitt, Tuan Anh Le, Joshua Tenenbaum; Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence (UAI), PMLR 124:1278-1287

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Flexible Approximate Inference via Stratified Normalizing Flows

Chris Cundy, Stefano Ermon; Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence (UAI), PMLR 124:1288-1297

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

Xinming Liu, Joseph Halpern; Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence (UAI), PMLR 124:1298-1307

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

Alexander Lyzhov, Yuliya Molchanova, Arsenii Ashukha, Dmitry Molchanov, Dmitry Vetrov; Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence (UAI), PMLR 124:1308-1317

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Non Parametric Graph Learning for Bayesian Graph Neural Networks

Soumyasundar Pal, Saber Malekmohammadi, Florence Regol, Yingxue Zhang, Yishi Xu, Mark Coates; Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence (UAI), PMLR 124:1318-1327

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Stable Policy Optimization via Off-Policy Divergence Regularization

Ahmed Touati, Amy Zhang, Joelle Pineau, Pascal Vincent; Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence (UAI), PMLR 124:1328-1337

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PoRB-Nets: Poisson Process Radial Basis Function Networks

Beau Coker, Melanie Fernandez Pradier, Finale Doshi-Velez; Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence (UAI), PMLR 124:1338-1347

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Deriving Bounds And Inequality Constraints Using Logical Relations Among Counterfactuals

Noam Finkelstein, Ilya Shpitser; Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence (UAI), PMLR 124:1348-1357

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Locally Masked Convolution for Autoregressive Models

Ajay Jain, Pieter Abbeel, Deepak Pathak; Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence (UAI), PMLR 124:1358-1367

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

Rishabh Singh, Jose Principe; Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence (UAI), PMLR 124:1368-1377

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OCEAN: Online Task Inference for Compositional Tasks with Context Adaptation

Hongyu Ren, Yuke Zhu, Jure Leskovec, Animashree Anandkumar, Animesh Garg; Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence (UAI), PMLR 124:1378-1387

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

Jakob Runge; Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence (UAI), PMLR 124:1388-1397

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