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Editors: Negar Kiyavash, Joris M. Mooij
Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence – Preface
; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:i-xi
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Convergence Behavior of an Adversarial Weak Supervision Method
Steven An, Sanjoy Dasgupta; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:1-49
Iterated INLA for State and Parameter Estimation in Nonlinear Dynamical Systems
Rafael Anderka, Marc Peter Deisenroth, So Takao; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:50-76
CSS: Contrastive Semantic Similarities for Uncertainty Quantification of LLMs
Shuang Ao, Stefan Rueger, Advaith Siddharthan; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:77-87
Unified PAC-Bayesian Study of Pessimism for Offline Policy Learning with Regularized Importance Sampling
Imad Aouali, Victor-Emmanuel Brunel, David Rohde, Anna Korba; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:88-109
Latent Representation Entropy Density for Distribution Shift Detection
Fabio Arnez, Daniel Alfonso Montoya Vasquez, Ansgar Radermacher, François Terrier; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:110-137
FedAST: Federated Asynchronous Simultaneous Training
Baris Askin, Pranay Sharma, Carlee Joe-Wong, Gauri Joshi; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:138-172
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Identifiability of total effects from abstractions of time series causal graphs
Charles K. Assaad, Emilie Devijver, Eric Gaussier, Gregor Goessler, Anouar Meynaoui; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:173-185
On the Capacitated Facility Location Problem with Scarce Resources
Gennaro Auricchio, Harry J. Clough, Jie Zhang; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:186-202
Mitigating Overconfidence in Out-of-Distribution Detection by Capturing Extreme Activations
Mohammad Azizmalayeri, Ameen Abu-Hanna, Giovanni Cinà; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:203-224
Inference in Probabilistic Answer Set Programs with Imprecise Probabilities via Optimization
Damiano Azzolini, Fabrizio Riguzzi; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:225-234
Differentially Private No-regret Exploration in Adversarial Markov Decision Processes
Shaojie Bai, Lanting Zeng, Chengcheng Zhao, Xiaoming Duan, Mohammad Sadegh Talebi, Peng Cheng, Jiming Chen; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:235-272
Walking the Values in Bayesian Inverse Reinforcement Learning
Ondrej Bajgar, Alessandro Abate, Konstantinos Gatsis, Michael Osborne; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:273-287
Learning Accurate and Interpretable Decision Trees
Maria-Florina Balcan, Dravyansh Sharma; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:288-307
Towards Bounding Causal Effects under Markov Equivalence
Alexis Bellot; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:308-332
Linearly Constrained Gaussian Processes are SkewGPs: application to Monotonic Preference Learning and Desirability
Alessio Benavoli, Dario Azzimonti; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:333-348
MetaCOG: A Heirarchical Probabilistic Model for Learning Meta-Cognitive Visual Representations
Marlene Berke, Zhangir Azerbayev, Mario Belledonne, Zenna Tavares, Julian Jara-Ettinger; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:349-359
[abs][Download PDF][OpenReview][Software][Supplementary PDF]
Shedding Light on Large Generative Networks: Estimating Epistemic Uncertainty in Diffusion Models
Lucas Berry, Axel Brando, David Meger; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:360-376
Publishing Number of Walks and Katz Centrality under Local Differential Privacy
Louis Betzer, Vorapong Suppakitpaisarn, Quentin Hillebrand; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:377-393
Using Autodiff to Estimate Posterior Moments, Marginals and Samples
Sam Bowyer, Thomas Heap, Laurence Aitchison; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:394-417
Polynomial Semantics of Tractable Probabilistic Circuits
Oliver Broadrick, Honghua Zhang, Guy Van den Broeck; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:418-429
Products, Abstractions and Inclusions of Causal Spaces
Simon Buchholz, Junhyung Park, Bernhard Schölkopf; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:430-449
Revisiting Kernel Attention with Correlated Gaussian Process Representation
Long Minh Bui, Tho Tran Huu, Duy Dinh, Tan Minh Nguyen, Trong Nghia Hoang; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:450-470
Sample Average Approximation for Black-Box Variational Inference
Javier Burroni, Justin Domke, Daniel Sheldon; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:471-498
Privacy-Aware Randomized Quantization via Linear Programming
Zhongteng Cai, Xueru Zhang, Mohammad Mahdi Khalili; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:499-516
Fair Active Learning in Low-Data Regimes
Romain Camilleri, Andrew Wagenmaker, Jamie Morgenstern, Lalit Jain, Kevin Jamieson; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:517-531
Multi-Relational Structural Entropy
Yuwei Cao, Hao Peng, Angsheng Li, Chenyu You, Zhifeng Hao, Philip S. Yu; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:532-546
How to Fix a Broken Confidence Estimator: Evaluating Post-hoc Methods for Selective Classification with Deep Neural Networks
Luı́s Felipe Cattelan, Danilo Silva; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:547-584
QuantProb: Generalizing Probabilities along with Predictions for a Pre-trained Classifier
Aditya Challa, Soma Dhavala, Snehanshu Saha; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:585-602
Generalization and Learnability in Multiple Instance Regression
Kushal Chauhan, Rishi Saket, Lorne Applebaum, Ashwinkumar Badanidiyuru, Chandan Giri, Aravindan Raghuveer; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:603-618
Gradient descent in matrix factorization: Understanding large initialization
Hengchao Chen, Xin Chen, Mohamad Elmasri, Qiang Sun; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:619-647
Conditional Bayesian Quadrature
Zonghao Chen, Masha Naslidnyk, Arthur Gretton, Francois-Xavier Briol; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:648-684
Adaptive Time-Stepping Schedules for Diffusion Models
Yuzhu Chen, Fengxiang He, Shi Fu, Xinmei Tian, Dacheng Tao; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:685-697
SMuCo: Reinforcement Learning for Visual Control via Sequential Multi-view Total Correlation
Tong Cheng, Hang Dong, Lu Wang, Bo Qiao, Qingwei Lin, Saravan Rajmohan, Thomas Moscibroda; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:698-717
Inference for Optimal Linear Treatment Regimes in Personalized Decision-making
Yuwen Cheng, Shu Yang; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:718-735
End-to-end Conditional Robust Optimization
Abhilash Reddy Chenreddy, Erick Delage; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:736-748
Differentiable Pareto-Smoothed Weighting for High-Dimensional Heterogeneous Treatment Effect Estimation
Yoichi Chikahara, Kansei Ushiyama; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:749-762
Fast Interactive Search under a Scale-Free Comparison Oracle
Daniyar Chumbalov, Lars Klein, Lucas Maystre, Matthias Grossglauser; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:763-786
Analysis of Bootstrap and Subsampling in High-dimensional Regularized Regression
Lucas Clarté, Adrien Vandenbroucque, Guillaume Dalle, Bruno Loureiro, Florent Krzakala, Lenka Zdeborová; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:787-819
Towards Minimax Optimality of Model-based Robust Reinforcement Learning
Pierre Clavier, Erwan Le Pennec, Matthieu Geist; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:820-855
Towards Representation Learning for Weighting Problems in Design-Based Causal Inference
Oscar Clivio, Avi Feller, Chris Holmes; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:856-880
Normalizing Flows for Conformal Regression
Nicolò Colombo; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:881-893
Power Mean Estimation in Stochastic Monte-Carlo Tree Search
Tuan Dam, Odalric-Ambrym Maillard, Emilie Kaufmann; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:894-918
Linear Opinion Pooling for Uncertainty Quantification on Graphs
Clemens Damke, Eyke Hüllermeier; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:919-929
Can we Defend Against the Unknown? An Empirical Study About Threshold Selection for Neural Network Monitoring
Khoi Tran Dang, Kevin Delmas, Jérémie Guiochet, Joris Guérin; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:930-942
Detecting critical treatment effect bias in small subgroups
Piersilvio De Bartolomeis, Javier Abad, Konstantin Donhauser, Fanny Yang; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:943-965
The Real Deal Behind the Artificial Appeal: Inferential Utility of Tabular Synthetic Data
Alexander Decruyenaere, Heidelinde Dehaene, Paloma Rabaey, Christiaan Polet, Johan Decruyenaere, Stijn Vansteelandt, Thomas Demeester; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:966-996
Discrete Probabilistic Inference as Control in Multi-path Environments
Tristan Deleu, Padideh Nouri, Nikolay Malkin, Doina Precup, Yoshua Bengio; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:997-1021
On Convergence of Federated Averaging Langevin Dynamics
Wei Deng, Qian Zhang, Yian Ma, Zhao Song, Guang Lin; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:1022-1054
Reflected Schrödinger Bridge for Constrained Generative Modeling
Wei Deng, Yu Chen, Nicole Tianjiao Yang, Hengrong Du, Qi Feng, Ricky Tian Qi Chen; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:1055-1082
Calibrated and Conformal Propensity Scores for Causal Effect Estimation
Shachi Deshpande, Volodymyr Kuleshov; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:1083-1111
Learning to Rank for Active Learning via Multi-Task Bilevel Optimization
Zixin Ding, Si Chen, Ruoxi Jia, Yuxin Chen; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:1112-1128
End-to-End Learning for Fair Multiobjective Optimization Under Uncertainty
My H. Dinh, James Kotary, Ferdinando Fioretto; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:1129-1145
Online Policy Optimization for Robust Markov Decision Process
Jing Dong, Jingwei Li, Baoxiang Wang, Jingzhao Zhang; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:1146-1175
Learning Distributionally Robust Tractable Probabilistic Models in Continuous Domains
Hailiang Dong, James Amato, Vibhav Gogate, Nicholas Ruozzi; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:1176-1188
Bandits with Knapsacks and Predictions
Davide Drago, Andrea Celli, Marek Elias; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:1189-1206
Approximate Bayesian Computation with Path Signatures
Joel Dyer, Patrick Cannon, Sebastian M. Schmon; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:1207-1231
Vertical Validation: Evaluating Implicit Generative Models for Graphs on Thin Support Regions
Mai Elkady, Thu Bui, Bruno Ribeiro, David Inouye; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:1232-1256
EntProp: High Entropy Propagation for Improving Accuracy and Robustness
Shohei Enomoto; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:1257-1270
Multi-fidelity Bayesian Optimization with Multiple Information Sources of Input-dependent Fidelity
Mingzhou Fan, Byung-Jun Yoon, Edward Dougherty, Nathan Urban, Francis Alexander, Raymundo Arróyave, Xiaoning Qian; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:1271-1293
Center-Based Relaxed Learning Against Membership Inference Attacks
Xingli Fang, Jung-Eun Kim; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:1294-1306
Enhancing Patient Recruitment Response in Clinical Trials: an Adaptive Learning Framework
Xinying Fang, Shouhao Zhou; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:1307-1322
Generalized Expected Utility as a Universal Decision Rule – A Step Forward
Hélène Fargier, Pierre Pomeret-Coquot; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:1323-1338
Last-iterate Convergence Separation between Extra-gradient and Optimism in Constrained Periodic Games
Yi Feng, Ping Li, Ioannis Panageas, Xiao Wang; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:1339-1370
Guaranteeing Robustness Against Real-World Perturbations In Time Series Classification Using Conformalized Randomized Smoothing
Nicola Franco, Jakob Spiegelberg, Jeanette Miriam Lorenz, Stephan Günnemann; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:1371-1388
Consistency Regularization for Domain Generalization with Logit Attribution Matching
Han Gao, Kaican Li, Weiyan Xie, Zhi Lin, Yongxiang Huang, Luning Wang, Caleb Cao, Nevin Zhang; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:1389-1407
Uncertainty Estimation with Recursive Feature Machines
Daniel Gedon, Amirhesam Abedsoltan, Thomas B. Schön, Mikhail Belkin; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:1408-1437
Bootstrap Your Conversions: Thompson Sampling for Partially Observable Delayed Rewards
Marco Gigli, Fabio Stella; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:1438-1452
GeONet: a neural operator for learning the Wasserstein geodesic
Andrew Gracyk, Xiaohui Chen; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:1453-1478
ContextFlow++: Generalist-Specialist Flow-based Generative Models with Mixed-variable Context Encoding
Denis Gudovskiy, Tomoyuki Okuno, Yohei Nakata; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:1479-1490
One Shot Inverse Reinforcement Learning for Stochastic Linear Bandits
Etash Guha, Jim James, Krishna Acharya, Vidya Muthukumar, Ashwin Pananjady; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:1491-1512
Characterizing Data Point Vulnerability as Average-Case Robustness
Tessa Han, Suraj Srinivas, Himabindu Lakkaraju; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:1513-1540
No-Regret Learning of Nash Equilibrium for Black-Box Games via Gaussian Processes
Minbiao Han, Fengxue Zhang, Yuxin Chen; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:1541-1557
Faster Perfect Sampling of Bayesian Network Structures
Juha Harviainen, Mikko Koivisto; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:1558-1568
Adjustment Identification Distance: A gadjid for Causal Structure Learning
Leonard Henckel, Theo Würtzen, Sebastian Weichwald; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:1569-1598
On Overcoming Miscalibrated Conversational Priors in LLM-based ChatBots
Christine Herlihy, Jennifer Neville, Tobias Schnabel, Adith Swaminathan; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:1599-1620
Neural Active Learning Meets the Partial Monitoring Framework
Maxime Heuillet, Ola Ahmad, Audrey Durand; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:1621-1639
Quantum Kernelized Bandits
Yasunari Hikima, Kazunori Murao, Sho Takemori, Yuhei Umeda; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:1640-1657
Recursively-Constrained Partially Observable Markov Decision Processes
Qi Heng Ho, Tyler Becker, Benjamin Kraske, Zakariya Laouar, Martin Feather, Federico Rossi, Morteza Lahijanian, Zachary Sunberg; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:1658-1680
Sound Heuristic Search Value Iteration for Undiscounted POMDPs with Reachability Objectives
Qi Heng Ho, Martin Feather, Federico Rossi, Zachary Sunberg, Morteza Lahijanian; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:1681-1697
A Global Markov Property for Solutions of Stochastic Difference Equations and the corresponding Full Time Graphs
Tom Hochsprung, Jakob Runge, Andreas Gerhardus; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:1698-1726
Revisiting Convergence of AdaGrad with Relaxed Assumptions
Yusu Hong, Junhong Lin; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:1727-1750
Equilibrium Computation in Multidimensional Congestion Games: CSP and Learning Dynamics Approaches
Mohammad T. Irfan, Hau Chan, Jared Soundy; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:1751-1779
Early-Exit Neural Networks with Nested Prediction Sets
Metod Jazbec, Patrick Forré, Stephan Mandt, Dan Zhang, Eric Nalisnick; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:1780-1796
On the Convergence of Hierarchical Federated Learning with Partial Worker Participation
Xiaohan Jiang, Hongbin Zhu; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:1797-1824
Adaptive Softmax Trees for Many-Class Classification
Rasul Kairgeldin, Magzhan Gabidolla, Miguel Carreira-Perpiñán; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:1825-1841
Towards Scalable Bayesian Transformers: Investigating stochastic subset selection for NLP
Peter Johannes Tejlgaard Kampen, Gustav Ragnar Stoettrup Als, Michael Riis Andersen; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:1842-1862
Low-rank Matrix Bandits with Heavy-tailed Rewards
Yue Kang, Cho-Jui Hsieh, Thomas Chun Man Lee; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:1863-1889
Cost-Sensitive Uncertainty-Based Failure Recognition for Object Detection
Moussa Kassem-Sbeyti, Michelle Karg, Christian Wirth, Nadja Klein, Sahin Albayrak; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:1890-1900
Probabilities of Causation for Continuous and Vector Variables
Yuta Kawakami, Manabu Kuroki, Jin Tian; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:1901-1921
Identification and Estimation of Conditional Average Partial Causal Effects via Instrumental Variable
Yuta Kawakami, Manabu Kuroki, Jin Tian; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:1922-1952
Targeted Reduction of Causal Models
Armin Kekić, Bernhard Schölkopf, Michel Besserve; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:1953-1980
Active Learning Framework for Incomplete Networks
Tung Khong, Cong Tran, Cuong Pham; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:1981-1998
Causal Discovery with Deductive Reasoning: One Less Problem
Jonghwan Kim, Inwoo Hwang, Sanghack Lee; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:1999-2017
ILP-FORMER: Solving Integer Linear Programming with Sequence to Multi-Label Learning
Shufeng Kong, Caihua Liu, Carla Gomes; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:2018-2028
How Inverse Conditional Flows Can Serve as a Substitute for Distributional Regression
Lucas Kook, Chris Kolb, Philipp Schiele, Daniel Dold, Marcel Arpogaus, Cornelius Fritz, Philipp Baumann, Philipp Kopper, Tobias Pielok, Emilio Dorigatti, David Rügamer; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:2029-2046
Distributionally Robust Optimization as a Scalable Framework to Characterize Extreme Value Distributions
Patrick Kuiper, Ali Hasan, Wenhao Yang, Yuting Ng, Hoda Bidkhori, Jose Blanchet, Vahid Tarokh; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:2047-2063
Optimization Framework for Semi-supervised Attributed Graph Coarsening
Manoj Kumar, Subhanu Halder, Archit Kane, Ruchir Gupta, Sandeep Kumar; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:2064-2075
Efficient Monte Carlo Tree Search via On-the-Fly State-Conditioned Action Abstraction
Yunhyeok Kwak, Inwoo Hwang, Dooyoung Kim, Sanghack Lee, Byoung-Tak Zhang; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:2076-2093
DataSP: A Differential All-to-All Shortest Path Algorithm for Learning Costs and Predicting Paths with Context
Alan Lahoud, Erik Schaffernicht, Johannes Stork; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:2094-2112
Quantifying Local Model Validity using Active Learning
Sven Lämmle, Can Bogoclu, Robert Vosshall, Anselm Haselhoff, Dirk Roos; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:2113-2135
Common Event Tethering to Improve Prediction of Rare Clinical Events
Quinn Lanners, Qin Weng, Marie-Louise Meng, Matthew M. Engelhard; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:2136-2162
Support Recovery in Sparse PCA with General Missing Data
Hanbyul Lee, Qifan Song, Jean Honorio; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:2163-2187
A General Identification Algorithm For Data Fusion Problems Under Systematic Selection
Jaron Jia Rong Lee, AmirEmad Ghassami, Ilya Shpitser; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:2188-2204
On the Inductive Biases of Demographic Parity-based Fair Learning Algorithms
Haoyu Lei, Amin Gohari, Farzan Farnia; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:2205-2225
Label Consistency-based Worker Filtering for Crowdsourcing
Jiao Li, Liangxiao Jiang, Chaoqun Li, Wenjun Zhang; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:2226-2237
Learning from Crowds with Dual-View K-Nearest Neighbor
Jiao Li, Liangxiao Jiang, Xue Wu, Wenjun Zhang; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:2238-2249
Optimizing Language Models for Human Preferences is a Causal Inference Problem
Victoria Lin, Eli Ben-Michael, Louis-Philippe Morency; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:2250-2270
Transductive and Inductive Outlier Detection with Robust Autoencoders
Ofir Lindenbaum, Yariv Aizenbud, Yuval Kluger; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:2271-2293
Hybrid CtrlFormer: Learning Adaptive Search Space Partition for Hybrid Action Control via Transformer-based Monte Carlo Tree Search
Jiashun Liu, Xiaotian Hao, Jianye Hao, Yan Zheng, Yujing Hu, Changjie Fan, Tangjie Lv, Zhipeng Hu; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:2294-2308
Patch-Prompt Aligned Bayesian Prompt Tuning for Vision-Language Models
Xinyang Liu, Dongsheng Wang, Bowei Fang, Miaoge Li, Yishi Xu, Zhibin Duan, Bo Chen, Mingyuan Zhou; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:2309-2330
Posterior Inference on Shallow Infinitely Wide Bayesian Neural Networks under Weights with Unbounded Variance
Jorge Loria, Anindya Bhadra; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:2331-2349
Local Discovery by Partitioning: Polynomial-Time Causal Discovery Around Exposure-Outcome Pairs
Jacqueline Maasch, Weishen Pan, Shantanu Gupta, Volodymyr Kuleshov, Kyra Gan, Fei Wang; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:2350-2382
Identifying Causal Changes Between Linear Structural Equation Models
Vineet Malik, Kevin Bello, Asish Ghoshal, Jean Honorio; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:2383-2398
BEARS Make Neuro-Symbolic Models Aware of their Reasoning Shortcuts
Emanuele Marconato, Samuele Bortolotti, Emile van Krieken, Antonio Vergari, Andrea Passerini, Stefano Teso; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:2399-2433
Amortized Variational Inference: When and Why?
Charles C. Margossian, David M. Blei; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:2434-2449
Learning relevant contextual variables within Bayesian optimization
Julien Martinelli, Ayush Bharti, Armi Tiihonen, S. T. John, Louis Filstroff, Sabina J. Sloman, Patrick Rinke, Samuel Kaski; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:2450-2470
Identifying Homogeneous and Interpretable Groups for Conformal Prediction
Natalia Martinez Gil, Dhaval Patel, Chandra Reddy, Giri Ganapavarapu, Roman Vaculin, Jayant Kalagnanam; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:2471-2485
Learning Causal Abstractions of Linear Structural Causal Models
Riccardo Massidda, Sara Magliacane, Davide Bacciu; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:2486-2515
Knowledge Intensive Learning of Credal Networks
Saurabh Mathur, Alessandro Antonucci, Sriraam Natarajan; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:2516-2526
Quantization of Large Language Models with an Overdetermined Basis
Daniil Merkulov, Daria Cherniuk, Alexander Rudikov, Ivan Oseledets, Ekaterina Muravleva, Aleksandr Mikhalev, Boris Kashin; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:2527-2536
Invariant Causal Prediction with Local Models
Alexander Mey, Rui M. Castro; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:2537-2559
Characterising Interventions in Causal Games
Manuj Mishra, James Fox, Michael Wooldridge; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:2560-2572
Approximation Algorithms for Observer Aware MDPs
Shuwa Miura, Olivier Buffet, Shlomo Zilberstein; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:2573-2586
Evaluating Bayesian deep learning for radio galaxy classification
Devina Mohan, Anna M. M. Scaife; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:2587-2597
Optimistic Regret Bounds for Online Learning in Adversarial Markov Decision Processes
Sang Bin Moon, Abolfazl Hashemi; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:2598-2622
Partial identification of the maximum mean discrepancy with mismeasured data
Ron Nafshi, Maggie Makar; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:2623-2645
General Markov Model for Solving Patrolling Games
Andrzej Nagórko, Marcin Waniek, Małgorzata Róg, Michał Godziszewski, Barbara Rosiak, Tomasz Paweł Michalak; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:2646-2669
Efficient Interactive Maximization of BP and Weakly Submodular Objectives
Adhyyan Narang, Omid Sadeghi, Lillian Ratliff, Maryam Fazel, Jeff Bilmes; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:2670-2699
Neural Architecture Search Finds Robust Models by Knowledge Distillation
Utkarsh Nath, Yancheng Wang, Yingzhen Yang; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:2700-2715
Extremely Greedy Equivalence Search
Achille Nazaret, David Blei; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:2716-2745
A Generalized Bayesian Approach to Distribution-on-Distribution Regression
Tin Lok James Ng; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:2746-2765
Cold-start Recommendation by Personalized Embedding Region Elicitation
Hieu Trung Nguyen, Duy Nguyen, Khoa Doan, Viet Anh Nguyen; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:2766-2786
Finite-Time Analysis of Three-Timescale Constrained Actor-Critic and Constrained Natural Actor-Critic Algorithms.
Prashansa Panda, Shalabh Bhatnagar; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:2787-2834
Quantifying Representation Reliability in Self-Supervised Learning Models
Young-Jin Park, Hao Wang, Shervin Ardeshir, Navid Azizan; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:2835-2860
Value-Based Abstraction Functions for Abstraction Sampling
Bobak Pezeshki, Kalev Kask, Alexander Ihler, Rina Dechter; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:2861-2901
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Non-stationary Domain Generalization: Theory and Algorithm
Thai-Hoang Pham, Xueru Zhang, Ping Zhang; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:2902-2927
Zero Inflation as a Missing Data Problem: a Proxy-based Approach
Trung Phung, Jaron Lee, Opeyemi Oladapo-Shittu, Eili Klein, Ayse Gurses, Susan Hannum, Kimberly Weems, Jill Marsteller, Sara Cosgrove, Sara Keller, Ilya Shpitser; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:2928-2955
DistriBlock: Identifying adversarial audio samples by leveraging characteristics of the output distribution
Matı́as Pizarro, Dorothea Kolossa, Asja Fisher; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:2956-2988
Neural Optimal Transport with Lagrangian Costs
Aram-Alexandre Pooladian, Carles Domingo-Enrich, Ricky T. Q. Chen, Brandon Amos; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:2989-3003
$χ$SPN: Characteristic Interventional Sum-Product Networks for Causal Inference in Hybrid Domains
Harsh Poonia, Moritz Willig, Zhongjie Yu, Matej Ze\vcević, Kristian Kersting, Devendra Singh Dhami; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:3004-3020
Graph Feedback Bandits with Similar Arms
Han Qi, Guo Fei, Li Zhu; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:3021-3040
Performative Reinforcement Learning in Gradually Shifting Environments
Ben Rank, Stelios Triantafyllou, Debmalya Mandal, Goran Radanovic; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:3041-3075
Decision-Focused Evaluation of Worst-Case Distribution Shift
Kevin Ren, Yewon Byun, Bryan Wilder; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:3076-3093
To smooth a cloud or to pin it down: Expressiveness guarantees and insights on score matching in denoising diffusion models
Teodora Reu, Francisco Vargas, Anna Kerekes, Michael Bronstein; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:3094-3120
Anomaly Detection with Variance Stabilized Density Estimation
Amit Rozner, Barak Battash, Henry Li, Lior Wolf, Ofir Lindenbaum; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:3121-3137
A Graph Theoretic Approach for Preference Learning with Feature Information
Aadirupa Saha, Arun Rajkumar; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:3138-3158
Label-wise Aleatoric and Epistemic Uncertainty Quantification
Yusuf Sale, Paul Hofman, Timo Löhr, Lisa Wimmer, Thomas Nagler, Eyke Hüllermeier; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:3159-3179
Unsupervised Feature Selection towards Pattern Discrimination Power
Wangduk Seo, Jaesung Lee; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:3180-3197
Cooperative Meta-Learning with Gradient Augmentation
Jongyun Shin, Seungjin Han, Jangho Kim; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:3198-3210
Response Time Improves Gaussian Process Models for Perception and Preferences
Michael Shvartsman, Benjamin Letham, Eytan Bakshy, Stephen Keeley; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:3211-3226
BanditQ:Fair Bandits with Guaranteed Rewards
Abhishek Sinha; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:3227-3244
Bayesian Active Learning in the Presence of Nuisance Parameters
Sabina J. Sloman, Ayush Bharti, Julien Martinelli, Samuel Kaski; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:3245-3263
Memorization Capacity for Additive Fine-Tuning with Small ReLU Networks
Jy-yong Sohn, Dohyun Kwon, Seoyeon An, Kangwook Lee; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:3264-3278
Computing Low-Entropy Couplings for Large-Support Distributions
Samuel Sokota, Dylan Sam, Christian Schroeder de Witt, Spencer Compton, Jakob Foerster, J. Zico Kolter; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:3279-3298
Multi-layer random features and the approximation power of neural networks
Rustem Takhanov; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:3299-3322
A Homogenization Approach for Gradient-Dominated Stochastic Optimization
Jiyuan Tan, Chenyu Xue, Chuwen Zhang, Qi Deng, Dongdong Ge, Yinyu Ye; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:3323-3344
Localised Natural Causal Learning Algorithms for Weak Consistency Conditions
Kai Teh, Kayvan Sadeghi, Terry Soo; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:3345-3355
Fast Reliability Estimation for Neural Networks with Adversarial Attack-Driven Importance Sampling
Karim Tit, Teddy Furon; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:3356-3367
Bayesian Pseudo-Coresets via Contrastive Divergence
Piyush Tiwary, Kumar Shubham, Vivek V. Kashyap, Prathosh A. P.; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:3368-3390
Offline Bayesian Aleatoric and Epistemic Uncertainty Quantification and Posterior Value Optimisation in Finite-State MDPs
Filippo Valdettaro, Aldo Faisal; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:3391-3409
Efficiently Deciding Algebraic Equivalence of Bow-Free Acyclic Path Diagrams
Thijs van Ommen; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:3410-3424
Random Linear Projections Loss for Hyperplane-Based Optimization in Neural Networks
Shyam Venkatasubramanian, Ahmed Aloui, Vahid Tarokh; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:3425-3447
Group Fairness in Predict-Then-Optimize Settings for Restless Bandits
Shresth Verma, Yunfan Zhao, Sanket Shah, Niclas Boehmer, Aparna Taneja, Milind Tambe; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:3448-3469
Model-Free Robust Reinforcement Learning with Sample Complexity Analysis
Yudan Wang, Shaofeng Zou, Yue Wang; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:3470-3513
Two Facets of SDE Under an Information-Theoretic Lens: Generalization of SGD via Training Trajectories and via Terminal States
Ziqiao Wang, Yongyi Mao; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:3514-3539
Pure Exploration in Asynchronous Federated Bandits
Zichen Wang, Chuanhao Li, Chenyu Song, Lianghui Wang, Quanquan Gu, Huazheng Wang; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:3540-3570
Metric Learning from Limited Pairwise Preference Comparisons
Zhi Wang, Geelon So, Ramya Korlakai Vinayak; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:3571-3602
AutoDrop: Training Deep Learning Models with Automatic Learning Rate Drop
Jing Wang, Yunfei Teng, Anna Choromanska; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:3603-3629
Bias-aware Boolean Matrix Factorization Using Disentangled Representation Learning
Xiao Wang, Jia Wang, Tong Zhao, Yijie Wang, Nan Zhang, Yong Zang, Sha Cao, Chi Zhang; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:3630-3642
Beyond Dirichlet-based Models: When Bayesian Neural Networks Meet Evidential Deep Learning
Hanjing Wang, Qiang Ji; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:3643-3665
Stein Random Feature Regression
Houston Warren, Rafael Oliveira, Fabio Ramos; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:3666-3688
Bounding causal effects with leaky instruments
David Watson, Jordan Penn, Lee Gunderson, Gecia Bravo-Hermsdorff, Afsaneh Mastouri, Ricardo Silva; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:3689-3710
Robust Entropy Search for Safe Efficient Bayesian Optimization
Dorina Weichert, Alexander Kister, Sebastian Houben, Patrick Link, Gunar Ernis; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:3711-3729
Hidden Population Estimation with Indirect Inference and Auxiliary Information
Justin Weltz, Eric Laber, Alexander Volfovsky; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:3730-3746
GCVR: Reconstruction from Cross-View Enable Sufficient and Robust Graph Contrastive Learning
Qianlong Wen, Zhongyu Ouyang, Chunhui Zhang, Yiyue Qian, Chuxu Zhang, Yanfang Ye; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:3747-3764
Understanding Pathologies of Deep Heteroskedastic Regression
Eliot Wong-Toi, Alex Boyd, Vincent Fortuin, Stephan Mandt; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:3765-3790
Functional Wasserstein Bridge Inference for Bayesian Deep Learning
Mengjing Wu, Junyu Xuan, Jie Lu; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:3791-3815
RE-SORT: Removing Spurious Correlation in Multilevel Interaction for CTR Prediction
Songli Wu, Liang Du, Jiaqi Yang, Yuai Wang, Dechuan Zhan, Shuang Zhao, Zixun Sun; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:3816-3828
Pix2Code: Learning to Compose Neural Visual Concepts as Programs
Antonia Wüst, Wolfgang Stammer, Quentin Delfosse, Devendra Singh Dhami, Kristian Kersting; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:3829-3852
Base Models for Parabolic Partial Differential Equations
Xingzi Xu, Ali Hasan, Jie Ding, Vahid Tarokh; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:3853-3878
\ensuremathα-Former: Local-Feature-Aware (L-FA) Transformer
Zhi Xu, Bin Sun, Yue Bai, Yun Fu; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:3879-3892
Functional Wasserstein Variational Policy Optimization
Junyu Xuan, Mengjing Wu, Zihe Liu, Jie Lu; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:3893-3911
Investigating the Impact of Model Width and Density on Generalization in Presence of Label Noise
Yihao Xue, Kyle Whitecross, Baharan Mirzasoleiman; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:3912-3935
Graph Contrastive Learning under Heterophily via Graph Filters
Wenhan Yang, Baharan Mirzasoleiman; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:3936-3955
Statistical and Causal Robustness for Causal Null Hypothesis Tests
Junhui Yang, Rohit Bhattacharya, Youjin Lee, Ted Westling; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:3956-3978
On Hardware-efficient Inference in Probabilistic Circuits
Lingyun Yao, Martin Trapp, Jelin Leslin, Gaurav Singh, Peng Zhang, Karthekeyan Periasamy, Martin Andraud; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:3979-3996
Masking the Unknown: Leveraging Masked Samples for Enhanced Data Augmentation
Xun Yao, Zijian Huang, Xinrong Hu, Jie Yang, Yi Guo; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:3997-4010
Domain Adaptation with Cauchy-Schwarz Divergence
Wenzhe Yin, Shujian Yu, Yicong Lin, Jie Liu, Jan-Jakob Sonke, Efstratios Gavves; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:4011-4040
Offline Reward Perturbation Boosts Distributional Shift in Online RL
Zishun Yu, Siteng Kang, Xinhua Zhang; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:4041-4055
Decentralized Online Learning in General-Sum Stackelberg Games
Yaolong Yu, Haipeng Chen; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:4056-4077
Probabilistic reconciliation of mixed-type hierarchical time series
Lorenzo Zambon, Dario Azzimonti, Nicolò Rubattu, Giorgio Corani; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:4078-4095
Dirichlet Continual Learning: Tackling Catastrophic Forgetting in NLP
Min Zeng, Haiqin Yang, Wei Xue, Qifeng Liu, Yike Guo; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:4096-4108
Causally Abstracted Multi-armed Bandits
Fabio Massimo Zennaro, Nicholas Bishop, Joel Dyer, Yorgos Felekis, Anisoara Calinescu, Michael Wooldridge, Theodoros Damoulas; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:4109-4139
Partial Identification with Proxy of Latent Confoundings via Sum-of-ratios Fractional Programming
Zhiheng Zhang, Xinyan Su; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:4140-4172
Decentralized Two-Sided Bandit Learning in Matching Market
Yirui Zhang, Zhixuan Fang; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:4173-4191
Learning Topological Representations with Bidirectional Graph Attention Network for Solving Job Shop Scheduling Problem
Cong Zhang, Zhiguang Cao, Yaoxin Wu, Wen Song, Jing Sun; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:4192-4208
Neighbor Similarity and Multimodal Alignment based Product Recommendation Study
Zhiqiang Zhang, Yongqiang Jiang, Qian Gao, Zhipeng Wang; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:4209-4218
Exploring High-dimensional Search Space via Voronoi Graph Traversing
Aidong Zhao, Xuyang Zhao, Tianchen Gu, Zhaori Bi, Xinwei Sun, Changhao Yan, Fan Yang, Dian Zhou, Xuan Zeng; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:4219-4236
Trusted re-weighting for label distribution learning
Zhuoran Zheng, Chen Wu, Yeying Jin, Xiuyi Jia; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:4237-4249
Approximate Kernel Density Estimation under Metric-based Local Differential Privacy
Yi Zhou, Yanhao Wang, Long Teng, Qiang Huang, Cen Chen; Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, PMLR 244:4250-4270
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