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Volume 180: Uncertainty in Artificial Intelligence, 1-5 August 2022, Eindhoven, The Netherlands

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Editors: James Cussens, Kun Zhang

[bib][citeproc]

Mutation-driven follow the regularized leader for last-iterate convergence in zero-sum games

Kenshi Abe, Mitsuki Sakamoto, Atsushi Iwasaki; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:1-10

NeuroBE: Escalating neural network approximations of Bucket Elimination

Sakshi Agarwal, Kalev Kask, Alex Ihler, Rina Dechter; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:11-21

Regret guarantees for model-based reinforcement learning with long-term average constraints

Mridul Agarwal, Qinbo Bai, Vaneet Aggarwal; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:22-31

GNN2GNN: Graph neural networks to generate neural networks

Andrea Agiollo, Andrea Omicini; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:32-42

Neuro-symbolic entropy regularization

Kareem Ahmed, Eric Wang, Kai-Wei Chang, Guy Van den Broeck; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:43-53

Non-parametric inference of relational dependence

Ragib Ahsan, Zahra Fatemi, David Arbour, Elena Zheleva; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:54-63

Data dependent randomized smoothing

Motasem Alfarra, Adel Bibi, Philip H. S. Torr, Bernard Ghanem; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:64-74

Multi-winner approval voting goes epistemic

Tahar Allouche, Jérôme Lang, Florian Yger; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:75-84

Inductive synthesis of finite-state controllers for POMDPs

Roman Andriushchenko, Milan Češka, Sebastian Junges, Joost-Pieter Katoen; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:85-95

Discovery of extended summary graphs in time series

Charles K. Assaad, Emilie Devijver, Eric Gaussier; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:96-106

Asymmetric DQN for partially observable reinforcement learning

Andrea Baisero, Brett Daley, Christopher Amato; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:107-117

Physics guided neural networks for spatio-temporal super-resolution of turbulent flows

Tianshu Bao, Shengyu Chen, Taylor T Johnson, Peyman Givi, Shervin Sammak, Xiaowei Jia; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:118-128

Byzantine-tolerant distributed multiclass sparse linear discriminant analysis

Yajie Bao, Weidong Liu, Xiaojun Mao, Weijia Xiong; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:129-138

Equilibrium aggregation: encoding sets via optimization

Sergey Bartunov, Fabian B. Fuchs, Timothy P. Lillicrap; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:139-149

Empirical bayes approach to truth discovery problems

Tsviel Ben Shabat, Reshef Meir, David Azriel; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:150-158

On early extinction and the effect of travelling in the SIR model

Petra Berenbrink, Colin Cooper, Cristina Gava, David Kohan Marzagão, Frederik Mallmann-Trenn, Tomasz Radzik; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:159-169

Learning soft interventions in complex equilibrium systems

Michel Besserve, Bernhard Schölkopf; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:170-180

Identifying near-optimal decisions in linear-in-parameter bandit models with continuous decision sets

Sanjay P. Bhat, Chaitanya Amballa; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:181-190

Offline change detection under contamination

Sujay Bhatt, Guanhua Fang, Ping Li; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:191-201

On testability of the front-door model via Verma constraints

Rohit Bhattacharya, Razieh Nabi; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:202-212

Robustness of model predictions under extension

Tineke Blom, Joris M. Mooij; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:213-222

Information theoretic approach to detect collusion in multi-agent games

Trevor Bonjour, Vaneet Aggarwal, Bharat Bhargava; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:223-232

Lifting in multi-agent systems under uncertainty

Tanya Braun, Marcel Gehrke, Florian Lau, Ralf Möller; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:233-243

On-the-fly adaptation of patrolling strategies in changing environments

Tomáš Brázdil, David Klaška, Antonı́n Kučera, Vı́t Musil, Petr Novotný, Vojtěch Řehák; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:244-254

On the inductive bias of neural networks for learning read-once DNFs

Ido Bronstein, Alon Brutzkus, Amir Globerson; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:255-265

AUTM flow: atomic unrestricted time machine for monotonic normalizing flows

Difeng Cai, Yuliang Ji, Huan He, Qiang Ye, Yuanzhe Xi; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:266-274

Active approximately metric-fair learning

Yiting Cao, Chao Lan; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:275-285

Capturing actionable dynamics with structured latent ordinary differential equations

Paidamoyo Chapfuwa, Sherri Rose, Lawrence Carin, Edward Meeds, Ricardo Henao; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:286-295

Privacy-aware compression for federated data analysis

Kamalika Chaudhuri, Chuan Guo, Mike Rabbat; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:296-306

The optimal noise in noise-contrastive learning is not what you think

Omar Chehab, Alexandre Gramfort, Aapo Hyvärinen; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:307-316

A competitive analysis of online failure-aware assignment

Mengjing Chen, Pingzhong Tang, Zihe Wang, Shenke Xiao, Xiwang Yang; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:317-325

Stackmix: a complementary mix algorithm

John Chen, Samarth Sinha, Anastasios Kyrillidis; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:326-335

Knowledge representation combining quaternion path integration and depth-wise atrous circular convolution

Xinyuan Chen, Zhongmei Zhou, Meichun Gao, Daya Shi, Mohd N. Husen; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:336-345

Sublinear time algorithms for greedy selection in high dimensions

Qi Chen, Kai Liu, Ruilong Yao, Hu Ding; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:346-356

Shoring up the foundations: fusing model embeddings and weak supervision

Mayee F. Chen, Daniel Y. Fu, Dyah Adila, Michael Zhang, Frederic Sala, Kayvon Fatahalian, Christopher Ré; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:357-367

On the definition and computation of causal treewidth

Yizuo Chen, Adnan Darwiche; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:368-377

Offline reinforcement learning under value and density-ratio realizability: The power of gaps

Jinglin Chen, Nan Jiang; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:378-388

Greedy modality selection via approximate submodular maximization

Runxiang Cheng, Gargi Balasubramaniam, Yifei He, Yao-Hung Hubert Tsai, Han Zhao; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:389-399

Feature selection for discovering distributional treatment effect modifiers

Yoichi Chikahara, Makoto Yamada, Hisashi Kashima; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:400-410

Combating the instability of mutual information-based losses via regularization

Kwanghee Choi, Siyeong Lee; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:411-421

A geometric method for improved uncertainty estimation in real-time

Gabriella Chouraqui, Liron Cohen, Gil Einziger, Liel Leman; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:422-432

Cyclic test time augmentation with entropy weight method

Sewhan Chun, Jae Young Lee, Junmo Kim; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:433-442

Greedy equivalence search in the presence of latent confounders

Tom Claassen, Ioan G. Bucur; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:443-452

Counterfactual inference of second Opinions

Nina L. Corvelo Benz, Manuel Gomez Rodriguez; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:453-463

Variational message passing neural network for Maximum-A-Posteriori (MAP) inference

Zijun Cui, Hanjing Wang, Tian Gao, Kartik Talamadupula, Qiang Ji; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:464-474

On provably robust meta-Bayesian optimization

Zhongxiang Dai, Yizhou Chen, Haibin Yu, Bryan Kian Hsiang Low, Patrick Jaillet; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:475-485

Individual fairness in feature-based pricing for monopoly markets

Shantanu Das, Swapnil Dhamal, Ganesh Ghalme, Shweta Jain, Sujit Gujar; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:486-495

Faster non-convex federated learning via global and local momentum

Rudrajit Das, Anish Acharya, Abolfazl Hashemi, Sujay Sanghavi, Inderjit S. Dhillon, Ufuk Topcu; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:496-506

Multi-objective Bayesian optimization over high-dimensional search spaces

Samuel Daulton, David Eriksson, Maximilian Balandat, Eytan Bakshy; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:507-517

Bayesian structure learning with generative flow networks

Tristan Deleu, António Góis, Chris Emezue, Mansi Rankawat, Simon Lacoste-Julien, Stefan Bauer, Yoshua Bengio; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:518-528

Bayesian spillover graphs for dynamic networks

Grace Deng, David S. Matteson; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:529-538

Multiclass classification for Hawkes processes

Christophe Denis, Charlotte Dion-Blanc, Laure Sansonnet; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:539-547

Quantification of Credal Uncertainty in Machine Learning: A Critical Analysis and Empirical Comparison

Eyke Hüllermeier, Sébastien Destercke, Mohammad Hossein Shaker; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:548-557

Balancing adaptability and non-exploitability in repeated games

Anthony DiGiovanni, Ambuj Tewari; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:559-568

Variational- and metric-based deep latent space for out-of-distribution detection

Or Dinari, Oren Freifeld; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:569-578

Revisiting DP-Means: fast scalable algorithms via parallelism and delayed cluster creation

Or Dinari, Oren Freifeld; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:579-588

X-MEN: guaranteed XOR-maximum entropy constrained inverse reinforcement learning

Fan Ding, Yexiang Xue; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:589-598

Improving sign-random-projection via count sketch

Punit Pankaj Dubey, Bhisham Dev Verma, Rameshwar Pratap, Keegan Kang; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:599-609

ResIST: Layer-wise decomposition of ResNets for distributed training

Chen Dun, Cameron R. Wolfe, Christopher M. Jermaine, Anastasios Kyrillidis; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:610-620

Learning explainable templated graphical models

Varun Embar, Sriram Srinivasa, Lise Getoor; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:621-630

SENTINEL: taming uncertainty with ensemble based distributional reinforcement learning

Hannes Eriksson, Debabrota Basu, Mina Alibeigi, Christos Dimitrakakis; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:631-640

Temporal abstractions-augmented temporally contrastive learning: An alternative to the Laplacian in RL

Akram Erraqabi, Marlos C. Machado, Mingde Zhao, Sainbayar Sukhbaatar, Alessandro Lazaric, Denoyer Ludovic, Yoshua Bengio; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:641-651

Implicit kernel meta-learning using kernel integral forms

John Isak Texas Falk, Carlo Cilibert, Massimiliano Pontil; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:652-662

Self-distribution distillation: efficient uncertainty estimation

Yassir Fathullah, Mark J. F. Gales; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:663-673

Sequential algorithmic modification with test data reuse

Jean Feng, Gene Pennllo, Nicholas Petrick, Berkman Sahiner, Romain Pirracchio, Alexej Gossmann; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:674-684

Estimating transfer entropy under long ranged dependencies

Sahil Garg, Umang Gupta, Yu Chen, Syamantak Datta Gupta, Yeshaya Adler, Anderson Schneider, Yuriy Nevmyvaka; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:685-695

Mitigating statistical bias within differentially private synthetic data

Sahra Ghalebikesabi, Harry Wilde, Jack Jewson, Arnaud Doucet, Sebastian Vollmer, Chris Holmes; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:696-705

Neural-progressive hedging: Enforcing constraints in reinforcement learning with stochastic programming

Supriyo Ghosh, Laura Wynter, Shiau Hong Lim, Duc Thien Nguyen; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:707-717

Do Bayesian variational autoencoders know what they don’t know?

Misha Glazunov, Apostolis Zarras; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:718-727

Robust expected information gain for optimal Bayesian experimental design using ambiguity sets

Jinwoo Go, Tobin Isaac; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:728-737

Efficient and transferable adversarial examples from bayesian neural networks

Martin Gubri, Maxime Cordy, Mike Papadakis, Yves Le Traon, Koushik Sen; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:738-748

Learning a neural Pareto manifold extractor with constraints

Soumyajit Gupta, Gurpreet Singh, Raghu Bollapragada, \Matthew Lease; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:749-758

Modeling extremes with $d$-max-decreasing neural networks

Ali Hasan, Khalil Elkhalil, Yuting Ng, João M. Pereira, Sina Farsiu, Jose Blanchet, Vahid Tarokh; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:759-768

Generalizing off-policy learning under sample selection bias

Tobias Hatt, Daniel Tschernutter, Stefan Feuerriegel; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:769-779

Reinforcement learning in many-agent settings under partial observability

Keyang He, Prashant Doshi, Bikramjit Banerjee; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:780-789

Variational multiple shooting for Bayesian ODEs with Gaussian processes

Pashupati Hegde, Çağatay Yıldız, Harri Lähdesmäki, Samuel Kaski, Markus Heinonen; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:790-799

Learning sparse representations of preferences within Choquet expected utility theory

Margot Herin, Patrice Perny, Nataliya Sokolovska; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:800-810

Quadratic metric elicitation for fairness and beyond

Gaurush Hiranandani, Jatin Mathur, Harikrishna Narasimhan, Oluwasanmi Koyejo; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:811-821

Fast predictive uncertainty for classification with Bayesian deep networks

Marius Hobbhahn, Agustinus Kristiadi, Philipp Hennig; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:822-832

CIGMO: Categorical invariant representations in a deep generative framework

Haruo Hosoya; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:833-843

Near-optimal Thompson sampling-based algorithms for differentially private stochastic bandits

Bingshan Hu, Nidhi Hegde; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:844-852

Uncertainty-aware pseudo-labeling for quantum calculations

Kexin Huang, Vishnu Sresht, Brajesh Rai, Mykola Bordyuh; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:853-862

A mutually exciting latent space Hawkes process model for continuous-time networks

Zhipeng Huang, Hadeel Soliman, Subhadeep Paul, Kevin S. Xu; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:863-873

Binary independent component analysis: a non-stationarity-based approach

Antti Hyttinen, Vitória Barin Pacela, Aapo Hyvärinen; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:874-884

Balancing utility and scalability in metric differential privacy

Jacob Imola, Shiva Kasiviswanathan, Stephen White, Abhinav Aggarwal, Nathanael Teissier; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:885-894

Towards painless policy optimization for constrained MDPs

Arushi Jain, Sharan Vaswani, Reza Babanezhad, Csaba Szepesvári, Doina Precup; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:895-905

Fedvarp: Tackling the variance due to partial client participation in federated learning

Divyansh Jhunjhunwala, Pranay Sharma, Aushim Nagarkatti, Gauri Joshi; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:906-916

Orthogonal Gromov-Wasserstein discrepancy with efficient lower bound

Hongwei Jin, Zishun Yu, Xinhua Zhang; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:917-927

If you’ve trained one you’ve trained them all: inter-architecture similarity increases with robustness

Haydn T. Jones, Jacob M. Springer, Garrett T. Kenyon, Juston S. Moore; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:928-937

Decision-theoretic planning with communication in open multiagent systems

Anirudh Kakarlapudi, Gayathri Anil, Adam Eck, Prashant Doshi, Leen-Kiat Soh; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:938-948

Optimal control of partially observable Markov decision processes with finite linear temporal logic constraints

Krishna C. Kalagarla, Kartik Dhruva, Dongming Shen, Rahul Jain, Ashutosh Nayyar, Pierluigi Nuzzo; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:949-958

Test for non-negligible adverse shifts

Vathy M Kamulete; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:959-968

Improved feature importance computation for tree models based on the Banzhaf value

Adam Karczmarz, Tomasz Michalak, Anish Mukherjee, Piotr Sankowski, Piotr Wygocki; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:969-979

Dynamic relocation in ridesharing via fixpoint construction

Ian A. Kash, Zhongkai Wen, Lenore D. Zuck; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:980-989

Restless and uncertain: Robust policies for restless bandits via deep multi-agent reinforcement learning

Jackson A. Killian, Lily Xu, Arpita Biswas, Milind Tambe; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:990-1000

Combinatorial Bayesian optimization with random mapping functions to convex polytopes

Jungtaek Kim, Seungjin Choi, Minsu Cho; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:1001-1011

On the effectiveness of adversarial training against common corruptions

Klim Kireev, Maksym Andriushchenko, Nicolas Flammarion; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:1012-1021

Revisiting the general identifiability problem

Yaroslav Kivva, Ehsan Mokhtarian, Jalal Etesami, Negar Kiyavash; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:1022-1030

Hitting times for continuous-time imprecise-Markov chains

Thomas Krak; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:1031-1040

Calibrated ensembles can mitigate accuracy tradeoffs under distribution shift

Ananya Kumar, Tengyu Ma, Percy Liang, Aditi Raghunathan; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:1041-1051

Greedy relaxations of the sparsest permutation algorithm

Wai-Yin Lam, Bryan Andrews, Joseph Ramsey; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:1052-1062

Interpolating between sampling and variational inference with infinite stochastic mixtures

Richard D. Lange, Ari S. Benjamin, Ralf M. Haefner, Xaq Pitkow; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:1063-1073

Systematized event-aware learning for multi-object tracking

Hyemin Lee, Daijin Kim; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:1074-1084

Fixing the Bethe approximation: How structural modifications in a graph improve belief propagation

Harald Leisenberger, Franz Pernkopf, Christian Knoll; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:1085-1095

Recursive Monte Carlo and variational inference with auxiliary variables

Alexander K. Lew, Marco Cusumano-Towner, Vikash K. Mansinghka; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:1096-1106

Solving structured hierarchical games using differential backward induction

Zun Li, Feiran Jia, Aditya Mate, Shahin Jabbari, Mithun Chakraborty, Milind Tambe, Yevgeniy Vorobeychik; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:1107-1117

PDQ-Net: Deep probabilistic dual quaternion network for absolute pose regression on $SE(3)$

Wenjie Li, Wasif Naeem, Jia Liu, Dequan Zheng, Wei Hao, Lijun Chen; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:1118-1127

Accelerating training of batch normalization: A manifold perspective

Mingyang Yi; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:1128-1137

Deep Dirichlet process mixture models

Naiqi Li, Wenjie Li, Yong Jiang, Shu-Tao Xia; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:1138-1147

Proportional allocation of indivisible resources under ordinal and uncertain preferences.

Zihao Li, Xiaohui Bei, Zhenzhen Yan; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:1148-1157

Efficient resource allocation with fairness constraints in restless multi-armed bandits

Dexun. Li, Pradeep Varakantham; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:1158-1167

A label efficient two-sample test

Weizhi Li, Gautam Dasarathy, Karthikeyan Natesan Ramamurthy, Visar Berisha; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:1168-1177

$\ell_∞$-Bounds of the MLE in the BTL Model under General Comparison Graphs

Wanshan Li, Shamindra Shrotriya, Alessandro Rinaldo; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:1178-1187

AdaCat: Adaptive categorical discretization for autoregressive models

Qiyang Li, Ajay Jain, Pieter Abbeel; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:1188-1198

Laplace approximated Gaussian process state-space models

Jakob Lindinger, Barbara Rakitsch, Christoph Lippert; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:1199-1209

Dimension reduction for high-dimensional small counts with KL divergence

Yurong Ling, Jing-Hao Xue; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:1210-1220

Federated online clustering of bandits

Xutong Liu, Haoru Zhao, Tong Yu, Shuai Li, John C.S. Lui; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:1221-1231

PathFlow: A normalizing flow generator that finds transition paths

Tianyi Liu, Weihao Gao, Zhirui Wang, Chong Wang; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:1232-1242

SASH: Efficient secure aggregation based on SHPRG for federated learning

Zizhen Liu, Si Chen, Jing Ye, Junfeng Fan, Huawei Li, Xiaowei Li; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:1243-1252

Offline policy optimization with eligible actions

Yao Liu, Yannis Flet-Berliac, Emma Brunskill; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:1253-1263

Data poisoning attacks on off-policy policy evaluation methods

Elita Lobo, Harvineet Singh, Marek Petrik, Cynthia Rudin, Himabindu Lakkaraju; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:1264-1274

Nonparametric exponential family graph embeddings for multiple representation learning

Chien Lu, Jaakko Peltonen, Timo Nummenmaa, Jyrki Nummenmaa; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:1275-1285

Local calibration: metrics and recalibration

Rachel Luo, Aadyot Bhatnagar, Yu Bai, Shengjia Zhao, Huan Wang, Caiming Xiong, Silvio Savarese, Stefano Ermon, Edward Schmerling, Marco Pavone; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:1286-1295

Data sampling affects the complexity of online SGD over dependent data

Shaocong Ma, Ziyi Chen, Yi Zhou, Kaiyi Ji, Yingbin Liang; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:1296-1305

Low-precision arithmetic for fast Gaussian processes

Wesley J. Maddox, Andres Potapcynski, Andrew Gordon Wilson; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:1306-1316

Perturbation type categorization for multiple adversarial perturbation robustness

Pratyush Maini, Xinyun Chen, Bo Li, Dawn Song; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:1317-1327

A causal bandit approach to learning good atomic interventions in presence of unobserved confounders

Aurghya Maiti, Vineet Nair, Gaurav Sinha; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:1328-1338

Case-based off-policy evaluation using prototype learning

Anton Matsson, Fredrik D. Johansson; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:1339-1349

Multistate analysis with infinite mixtures of Markov chains

Lucas Maystre, Tiffany Wu, Roberto Sanchis-Ojeda, Tony Jebara; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:1350-1359

Forget-me-not! Contrastive critics for mitigating posterior collapse

Sachit Menon, David Blei, Carl Vondrick; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:1360-1370

Can mean field control (mfc) approximate cooperative multi agent reinforcement learning (marl) with non-uniform interaction?

Washim Uddin Mondal, Vaneet Aggarwal, Satish V. Ukkusuri; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:1371-1380

Monotonicity regularization: Improved penalties and novel applications to disentangled representation learning and robust classification

João Monteiro, Mohamed Osama Ahmed, Hoseein Hajimirsadeghi, Greg Mori; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:1381-1391

Set-valued prediction in hierarchical classification with constrained representation complexity

Thomas Mortier, Eyke Hüllermeier, Krzysztof Dembczyński, Willem Waegeman; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:1392-1401

Safety aware changepoint detection for piecewise i.i.d. bandits

Subhojyoti Mukherjee; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:1402-1412

ReVar: Strengthening policy evaluation via reduced variance sampling

Subhojyoti Mukherjee, Josiah P. Hanna, Robert D Nowak; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:1413-1422

Probabilistic surrogate networks for simulators with unbounded randomness

Andreas Munk, Berend Zwartsenberg, Adam Ścibior, Atılım Güneş G. Baydin, Andrew Stewart, Goran Fernlund, Anoush Poursartip, Frank Wood; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:1423-1433

Data augmentation in Bayesian neural networks and the cold posterior effect

Seth Nabarro, Stoil Ganev, Adrià Garriga-Alonso, Vincent Fortuin, Mark van der Wilk, Laurence Aitchison; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:1434-1444

Semiparametric causal sufficient dimension reduction of multidimensional treatments

Razieh Nabi, Todd McNutt, Ilya Shpitser; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:1445-1455

Partially adaptive regularized multiple regression analysis for estimating linear causal effects

Hisayoshi Nanmo, Manabu Kuroki; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:1456-1465

Efficient learning of sparse and decomposable PDEs using random projection

Md Nasim, Xinghang Zhang, Anter El-Azab, Yexiang Xue; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:1466-1476

Linearizing contextual bandits with latent state dynamics

Elliot Nelson, Debarun Bhattacharjya, Tian Gao, Miao Liu, Djallel Bouneffouf, Pascal Poupart; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:1477-1487

CounteRGAN: Generating counterfactuals for real-time recourse and interpretability using residual GANs

Daniel Nemirovsky, Nicolas Thiebaut, Ye Xu, Abhishek Gupta; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:1488-1497

Robust Bayesian recourse

Tuan-Duy H. Nguyen, Ngoc Bui, Duy Nguyen, Man-Chung Yue, Viet Anh Nguyen; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:1498-1508

Efficient and accurate top-k recovery from choice data

Duc Nguyen; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:1509-1518

Cycle class consistency with distributional optimal transport and knowledge distillation for unsupervised domain adaptation

Tuan Nguyen, Van Nguyen, Trung Le, He Zhao, Quan Hung Tran, Dinh Phung; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:1519-1529

Ordinal causal discovery

Yang Ni, Bani Mallick; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:1530-1540

An explore-then-commit algorithm for submodular maximization under full-bandit feedback

Guanyu Nie, Mridul Agarwal, Abhishek Kumar Umrawal, Vaneet Aggarwal, Christopher John Quinn; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:1541-1551

Evaluating high-order predictive distributions in deep learning

Ian Osband, Zheng Wen, Seyed Mohammad Asghari, Vikranth Dwaracherla, Xiuyuan Lu, Benjamin Van Roy; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:1552-1560

Understanding and mitigating the limitations of prioritized experience replay

Yangchen Pan, Jincheng Mei, Amir-massoud Farahmand, Martha White, Hengshuai Yao, Mohsen Rohani, Jun Luo; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:1561-1571

Robust learning of tractable probabilistic models

Rohith Peddi, Tahrima Rahman, Vibhav Gogate; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:1572-1581

Attribution of predictive uncertainties in classification models

Iker Perez, Piotr Skalski, Alec Barns-Graham, Jason Wong, David Sutton; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:1582-1591

Learning large Bayesian networks with expert constraints

Vaidyanathan Peruvemba Ramaswamy, Stefan Szeider; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:1592-1601

AND/OR branch-and-bound for computational protein design optimizing K*

Bobak Pezeshki, Radu Marinescu, Alexander Ihler, Rina Dechter; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:1602-1612

Identifiability of sparse causal effects using instrumental variables

Niklas Pfister, Jonas Peters; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:1613-1622

Bayesian quantile and expectile optimisation

Victor Picheny, Henry Moss, Léonard Torossian, Nicolas Durrande; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:1623-1633

Using hierarchies to efficiently combine evidence with Dempster’s rule of combination

Daira Pinto Prieto, Ronald de Haan; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:1634-1643

Voronoi density estimator for high-dimensional data: Computation, compactification and convergence

Vladislav Polianskii, Giovanni Luca Marchetti, Alexander Kravberg, Anastasiia Varava, Florian T. Pokorny, Danica Kragic; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:1644-1653

Clustering a union of linear subspaces via matrix factorization and innovation search

Mostafa Rahmani; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:1654-1664

Learning in Markov games: Can we exploit a general-sum opponent?

Giorgia Ramponi, Marcello Restelli; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:1665-1675

Expectation programming: Adapting probabilistic programming systems to estimate expectations efficiently

Tim Reichelt, Adam Goliński, Luke Ong, Tom Rainforth; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:1676-1685

A free lunch from the noise: Provable and practical exploration for representation learning

Tongzheng Ren, Tianjun Zhang, Csaba Szepesvári, Bo Dai; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:1686-1696

Quantum perceptron revisited: Computational-statistical tradeoffs

Mathieu Roget, Giuseppe Di Molfetta, Hachem Kadri; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:1697-1706

Resolving label uncertainty with implicit posterior models

Esther Rolf, Nikolay Malkin, Alexandros Graikos, Ana Jojic, Caleb Robinson, Nebojsa Jojic; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:1707-1717

Feature learning and random features in standard finite-width convolutional neural networks: An empirical study

Maxim Samarin, Volker Roth, David Belius; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:1718-1727

Robust identifiability in linear structural equation models of causal inference

Karthik A. Sankararaman, Anand Louis, Navin Goyal; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:1728-1737

How unfair is private learning?

Amartya Sanyal, Yaxi Hu, Fanny Yang; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:1738-1748

Probabilistic spatial transformer networks

Pola Schwöbel, Frederik Rahbæk Warburg, Martin Jørgensen, Kristoffer Hougaard Madsen, Søren Hauberg; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:1749-1759

Learning functions on multiple sets using multi-set transformers

Kira A. Selby, Ahmad Rashid, Ivan Kobyzev, Mehdi Rezagholizadeh, Pascal Poupart; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:1760-1770

SymNet 2.0: Effectively handling Non-Fluents and Actions in Generalized Neural Policies for RDDL Relational MDPs

Vishal Sharma, Daman Arora, Florian Geißer, Mausam , Parag Singla; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:1771-1781

Reframed GES with a neural conditional dependence measure

Xinwei Shen, Shengyu Zhu, Jiji Zhang, Shoubo Hu, Zhitang Chen; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:1782-1791

Conditional simulation using diffusion Schrödinger bridges

Yuyang Shi, Valentin De Bortoli, George Deligiannidis, Arnaud Doucet; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:1792-1802

Neural ensemble search via Bayesian sampling

Yao Shu, Yizhou Chen, Zhongxiang Dai, Bryan Kian Hsiang Low; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:1803-1812

Shifted compression framework: generalizations and improvements

Egor Shulgin, Peter Richtárik; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:1813-1823

PAC-Bayesian domain adaptation bounds for multiclass learners

Anthony Sicilia, Katherine Atwell, Malihe Alikhani, Seong Jae Hwang; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:1824-1834

VQ-Flows: Vector quantized local normalizing flows

Sahil Sidheekh, Chris B. Dock, Tushar Jain, Radu Balan, Maneesh K. Singh; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:1835-1845

Enhanced adaptive optics control with image to image translation

Jeffrey Smith, Jesse Cranney, Charles Gretton, Damien Gratadour; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:1846-1856

Fast inference and transfer of compositional task structures for few-shot task generalization

Sungryull Sohn, Hyunjae Woo, Jongwook Choi, Lyubing Qiang, Izzeddin Gur, Aleksandra Faust, Honglak Lee; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:1857-1865

Mutual information based Bayesian graph neural network for few-shot learning

Kaiyu Song, Kun Yue, Liang Duan, Mingze Yang, Angsheng Li; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:1866-1875

SMT-based weighted model integration with structure awareness

Giuseppe Spallitta, Gabriele Masina, Paolo Morettin, Andrea Passerini, Roberto Sebastiani; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:1876-1885

A robustness test for estimating total effects with covariate adjustment

Zehao Su, Leonard Henckel; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:1886-1895

Simplified and unified analysis of various learning problems by reduction to Multiple-Instance Learning

Daiki Suehiro, Eiji Takimoto; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:1896-1906

Marginal MAP estimation for inverse RL under occlusion with observer noise

Prasanth Sengadu Suresh, Prashant Doshi; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:1907-1916

High-probability bounds for robust stochastic Frank-Wolfe algorithm

Tongyi Tang, Krishna Balasubramanian, Thomas Chun Man Lee; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:1917-1927

Contrastive latent variable models for neural text generation

Zhiyang Teng, Chenhua Chen, Yan Zhang, Yue Zhang; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:1928-1938

Semi-supervised novelty detection using ensembles with regularized disagreement

Alexandru Tifrea, Eric Stavarache, Fanny Yang; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:1939-1948

Efficient inference for dynamic topic modeling with large vocabularies

Federico Tomasi, Mounia Lalmas, Zhenwen Dai; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:1950-1959

Learning linear non-Gaussian polytree models

Daniele Tramontano, Anthea Monod, Mathias Drton; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:1960-1969

Multi-source domain adaptation via weighted joint distributions optimal transport

Rosanna Turrisi, Rémi Flamary, Alain Rakotomamonjy, Massimiliano Pontil; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:1970-1980

Towards unsupervised open world semantic segmentation

Svenja Uhlemeyer, Matthias Rottmann, Hanno Gottschalk; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:1981-1991

Learning invariant weights in neural networks

Tycho F.A. van der Ouderaa, Mark van der Wilk; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:1992-2001

Causal forecasting: generalization bounds for autoregressive models

Leena Chennuru Vankadara, Philipp Michael Faller, Michaela Hardt, Lenon Minorics, Debarghya Ghoshdastidar, Dominik Janzing; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:2002-2012

Intervention target estimation in the presence of latent variables

Burak Varici, Karthikeyan Shanmugam, Prasanna Sattigeri, Ali Tajer; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:2013-2023

Bayesian federated estimation of causal effects from observational data

Thanh Vinh Vo, Young Lee, Trong Nghia Hoang, Tze-Yun Leong; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:2024-2034

Bias aware probabilistic Boolean matrix factorization

Changlin Wan, Pengtao Dang, Tong Zhao, Yong Zang, Chi Zhang, Sha Cao; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:2035-2044

Meta-learning without data via Wasserstein distributionally-robust model fusion

Zhenyi Wang, Xiaoyang Wang, Li Shen, Qiuling Suo, Kaiqiang Song, Dong Yu, Yan Shen, Mingchen Gao; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:2045-2055

Detecting textual adversarial examples through randomized substitution and vote

Xiaosen Wang, Xiong Yifeng, Kun He; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:2056-2065

ST-MAML : A stochastic-task based method for task-heterogeneous meta-learning

Zhe Wang, Jake Grigsby, Arshdeep Sekhon, Yanjun Qi; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:2066-2074

Toward learning human-aligned cross-domain robust models by countering misaligned features

Haohan Wang, Zeyi Huang, Hanlin Zhang, Yong Jae Lee, Eric P. Xing; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:2075-2084

Generalized Bayesian quadrature with spectral kernels

Houston Warren, Rafael Oliveira, Fabio Ramos; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:2085-2095

Causal discovery under a confounder blanket

David S. Watson, Ricardo Silva; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:2096-2106

A new constructive criterion for Markov equivalence of MAGs

Marcel Wienöbst, Max Bannach, Maciej Liśkiewicz; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:2107-2116

Residual bootstrap exploration for stochastic linear bandit

Shuang Wu, Chi-Hua Wang, Yuantong Li, Guang Cheng; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:2117-2127

Differentially private multi-party data release for linear regression

Ruihan Wu, Xin Yang, Yuanshun Yao, Jiankai Sun, Tianyi Liu, Q. Kilian Weinberger, Chong Wang; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:2128-2137

Partial likelihood Thompson sampling

Han Wu, Stefan Wager; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:2138-2147

Fine-Grained matching with multi-perspective similarity modeling for cross-modal retrieval

Xiumin Xie, Chuanwen Hou, Zhixin Li; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:2148-2158

Deterministic policy gradient: Convergence analysis

Huaqing. Xiong, Tengyu Xu, Lin Zhao, Yingbin Liang, Wei Zhang; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:2159-2169

Finite-horizon equilibria for neuro-symbolic concurrent stochastic games

Rui Yan, Gabriel Santos, Xiaoming Duan, David Parker, Marta Kwiatkowska; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:2170-2180

Addressing token uniformity in transformers via singular value transformation

Hanqi Yan, Lin Gui, Wenjie Li, Yulan He; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:2181-2191

Differentially private SGDA for minimax problems

Zhenhuan Yang, Shu Hu, Yunwen Lei, Kush R Vashney, Siwei Lyu, Yiming Ying; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:2192-2202

Self-supervised representations for multi-view reinforcement learning

Huanhuan Yang, Dianxi Shi, Guojun Xie, Yingxuan Peng, Yi Zhang, Yantai Yang, Shaowu Yang; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:2203-2213

Robust textual embedding against word-level adversarial attacks

Yichen Yang, Xiaosen Wang, Kun He; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:2214-2224

CoSPA: An improved masked language model with copy mechanism for Chinese spelling correction

Shoujian Yang, Lian Yu; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:2225-2234

Noisy L0-sparse subspace clustering on dimensionality reduced data

Yingzhen Yang, Ping Li; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:2235-2245

Pareto navigation gradient descent: a first-order algorithm for optimization in pareto set

Mao Ye, Qiang Liu; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:2246-2255

Future gradient descent for adapting the temporal shifting data distribution in online recommendation systems

Mao Ye, Ruichen Jiang, Haoxiang Wang, Dhruv Choudhary, Xiaocong Du, Bhargav Bhushanam, Aryan Mokhtari, Arun Kejariwal, Qiang Liu; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:2256-2266

Superposing many tickets into one: A performance booster for sparse neural network training

Lu Yin, Vlado Menkovski, Meng Fang, Tianjin Huang, Yulong Pei, Mykola Pechenizkiy; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:2267-2277

Offline stochastic shortest path: Learning, evaluation and towards optimality

Ming Yin, Wenjing Chen, Mengdi Wang, Yu-Xiang Wang; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:2278-2288

Active learning with label comparisons

Gal Yona, Shay Moran, Gal Elidan, Amir Globerson; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:2289-2298

Cross-domain adaptive transfer reinforcement learning based on state-action correspondence

Heng You, Tianpei Yang, Yan Zheng, Jianye Hao, E. Taylor Matthew; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:2299-2309

Learning binary multi-scale games on networks

Sixie Yu, P. Jeffrey Brantingham, Matthew Valasik, Yevgeniy Vorobeychik; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:2310-2319

Predictive Whittle networks for time series

Zhongjie Yu, Fabrizio Ventola, Nils Thoma, Devendra Singh Dhami, Martin Mundt, Kristian Kersting; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:2320-2330

Principle of relevant information for graph sparsification

Shujian Yu, Francesco Alesiani, Wenzhe Yin, Robert Jenssen, Jose C. Principe; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:2331-2341

Asymptotic optimality for active learning processes

Xueying Zhan, Yaowei Wang, Antoni B. Chan; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:2342-2352

Distributed adversarial training to robustify deep neural networks at scale

Gaoyuan Zhang, Songtao Lu, Yihua Zhang, Xiangyi Chen, Pin-Yu Chen, Quanfu Fan, Lee Martie, Lior Horesh, Mingyi Hong, Sijia Liu; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:2353-2363

Stability of SGD: Tightness analysis and improved bounds

Yikai Zhang, Wenjia Zhang, Sammy Bald, Vamsi Pingali, Chao Chen, Mayank Goswami; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:2364-2373

Research on video adversarial attack with long living cycle

Zeyu Zhao, Ke Xu, Xinghao Jiang, Tanfeng Sun; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:2374-2382

Causal discovery with heterogeneous observational data

Fangting Zhou, Kejun He, Yang Ni; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:2383-2393

Convergence Analysis of Linear Coupling with Inexact Proximal Operator

Qiang Zhou, Sinno Jialin Pan; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:2394-2403

Information design for multiple independent and self-interested defenders: Work less, pay off more

Chenghan Zhou, Andrew Spivey, Haifeng Xu, Thanh Hong Nguyen; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:2404-2413

Causal inference with treatment measurement error: a nonparametric instrumental variable approach

Yuchen Zhu, Limor Gultchin, Arthur Gretton, Matt J. Kusner, Ricardo Silva; Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR 180:2414-2424

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