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Editors: James Cussens, Kun Zhang
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Mutation-driven follow the regularized leader for last-iterate convergence in zero-sum games
; 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
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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