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Editors: Silvia Chiappa, Sara Magliacane
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Aggregating Data for Optimal Learning
; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:1-30
Causal Inference amid Missingness-Specific Independences and Mechanism Shifts
Johan de Aguas, Leonard Henckel, Johan Pensar, Guido Biele; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:31-44
Conformal Prediction for Federated Graph Neural Networks with Missing Neighbor Information
Ömer Faruk Akgül, Rajgopal Kannan, Viktor Prasanna; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:45-63
CATE Estimation With Potential Outcome Imputation From Local Regression
Ahmed Aloui, Juncheng Dong, Cat Phuoc Le, Vahid Tarokh; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:64-90
Conditional Average Treatment Effect Estimation Under Hidden Confounders
Ahmed Aloui, Juncheng Dong, Ali Hasan, Vahid Tarokh; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:91-110
Sparse Structure Exploration and Re-optimization for Vision Transformer
Sangho An, Jinwoo Kim, Keonho Lee, Jingang Huh, Chanwoong Kwak, Yujin Lee, Moonsub Jin, Jangho Kim; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:111-131
Symbiotic Local Search for Small Decision Tree Policies in MDPs
Roman Andriushchenko, Milan Ceska, Debraj Chakraborty, Sebastian Junges, Jan Kretinsky, Filip Macák; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:132-148
MOHITO: Multi-Agent Reinforcement Learning using Hypergraphs for Task-Open Systems
Gayathri Anil, Prashant Doshi, Daniel Alan Redder, Adam Eck, Leen-Kiat Soh; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:149-171
Expert-In-The-Loop Causal Discovery: Iterative Model Refinement Using Expert Knowledge
Ankur Ankan, Johannes Textor; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:172-183
Evasion Attacks Against Bayesian Predictive Models
Pablo G. Arce, Roi Naveiro, David Ríos Insua; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:184-202
Hybrid Bernstein Normalizing Flows for Flexible Multivariate Density Regression with Interpretable Marginals
Marcel Arpogaus, Thomas Kneib, Thomas Nagler, David Rügamer; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:203-222
Lower Bound on Howard Policy Iteration for Deterministic Markov Decision Processes
Ali Asadi, Krishnendu Chatterjee, Jakob de Raaij; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:223-237
Limit-sure Reachability for Small Memory Policies in POMDPs is NP-complete
Ali Asadi, Krishnendu Chatterjee, Raimundo Saona, Ali Shafiee; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:238-256
Can a Bayesian Oracle Prevent Harm from an Agent?
Yoshua Bengio, Michael K. Cohen, Nikolay Malkin, Matt MacDermott, Damiano Fornasiere, Pietro Greiner, Younesse Kaddar; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:257-270
Revisiting the Berkeley Admissions data: Statistical Tests for Causal Hypotheses
Sourbh Bhadane, Joris Marten Mooij, Philip Boeken, Onno Zoeter; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:271-295
Asymptotically Optimal Linear Best Feasible Arm Identification with Fixed Budget
Jie Bian, Vincent Y. F. Tan; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:296-331
BELIEF - Bayesian Sign Entropy Regularization for LIME Framework
Revoti Prasad Bora, Philipp Terhörst, Raymond Veldhuis, Raghavendra Ramachandra, Kiran Raja; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:332-354
Multi-Cost-Bounded Reachability Analysis of POMDPs
Alexander Bork, Joost-Pieter Katoen, Tim Quatmann, Svenja Stein; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:355-387
Using Submodular Optimization to Approximate Minimum-Size Abductive Path Explanations for Tree-Based Models
Louenas Bounia; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:388-397
Stein Variational Evolution Strategies
Cornelius V. Braun, Robert Tjarko Lange, Marc Toussaint; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:398-420
Causal Models for Growing Networks
Gecia Bravo-Hermsdorff, Kayvan Sadeghi, Lee M. Gunderson; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:421-442
Epistemic Uncertainty in Conformal Scores: A Unified Approach
Luben Miguel Cruz Cabezas, Vagner Silva Santos, Thiago Ramos, Rafael Izbicki; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:443-470
Creative Agents: Empowering Agents with Imagination for Creative Tasks
Penglin Cai, Chi Zhang, Yuhui Fu, Haoqi Yuan, Zongqing Lu; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:471-496
Fast Non-convex Matrix Sensing with Optimal Sample Complexity
Jian-Feng Cai, Tong Wu, Ruizhe Xia; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:497-520
Out-of-distribution Robust Optimization
Zhongze Cai, Hansheng Jiang, Xiaocheng Li; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:521-539
Unsupervised Attributed Dynamic Network Embedding with Stability Guarantees
Emma Ceccherini, Ian Gallagher, Andrew Jones, Daniel John Lawson; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:540-567
Improving Graph Contrastive Learning with Community Structure
Xiang Chen, Kun Yue, Liang Duan, Lixing Yu; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:568-585
Just Trial Once: Ongoing Causal Validation of Machine Learning Models
Jacob M. Chen, Michael Oberst; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:586-611
Adaptive Threshold Sampling for Pure Exploration in Submodular Bandits
Wenjing Chen, Shuo Xing, Victoria G. Crawford; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:612-646
Tuning-Free Coreset Markov Chain Monte Carlo via Hot DoG
Naitong Chen, Jonathan H. Huggins, Trevor Campbell; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:647-672
NRFlow: Towards Noise-Robust Generative Modeling via High-Order Mechanism
Bo Chen, Chengyue Gong, Xiaoyu Li, Yingyu Liang, Zhizhou Sha, Zhenmei Shi, Zhao Song, Mingda Wan, Xugang Ye; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:673-704
Moment Alignment: Unifying Gradient and Hessian Matching for Domain Generalization
Yuen Chen, Haozhe Si, Guojun Zhang, Han Zhao; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:705-736
Selective Blocking for Message-Passing Neural Networks on Heterophilic Graphs
Yoonhyuk Choi, Taewook Ko, Jiho Choi, Chong-Kwon Kim; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:737-751
Well-Defined Function-Space Variational Inference in Bayesian Neural Networks via Regularized KL-Divergence
Tristan Cinquin, Robert Bamler; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:752-776
Optimal Transport for Probabilistic Circuits
Adrian Ciotinga, YooJung Choi; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:777-797
Building Conformal Prediction Intervals with Approximate Message Passing
Lucas Clarté, Lenka Zdeborová; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:798-820
RL, but don’t do anything I wouldn’t do
Michael K. Cohen, Marcus Hutter, Yoshua Bengio, Stuart Russell; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:821-836
Measuring IIA Violations in Similarity Choices with Bayesian Models
Hugo Sales Correa, Suryanarayana Sankagiri, Daniel R. Figueiredo, Matthias Grossglauser; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:837-862
The Relativity of Causal Knowledge
Gabriele D’Acunto, Claudio Battiloro; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:863-881
Online Learning with Stochastically Partitioning Experts
Puranjay Datta, Sharayu Moharir, Jaya Prakash Champati; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:882-896
ELBO, regularized maximum likelihood, and their common one-sample approximation for training stochastic neural networks
Sina Däubener, Simon Damm, Asja Fischer; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:897-914
Optimal Submanifold Structure in Log-linear Models
Zhou Derun, Mahito Sugiyama; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:915-932
Calibrated Regression Against An Adversary Without Regret
Shachi Deshpande, Charles Marx, Volodymyr Kuleshov; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:933-958
Cutting Through Privacy: A Hyperplane-Based Data Reconstruction Attack in Federated Learning
Francesco Diana, André Nusser, Chuan Xu, Giovanni Neglia; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:959-980
Valid Bootstraps for Network Embeddings with Applications to Network Visualisation
Emerald Dilworth, Ed Davis, Daniel John Lawson; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:981-1002
Nearly Optimal Differentially Private ReLU Regression
Meng Ding, Mingxi Lei, Shaowei Wang, Tianhang Zheng, Di Wang, Jinhui Xu; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:1003-1038
Simulation-based Inference for High-dimensional Data using Surjective Sequential Neural Likelihood Estimation
Simon Dirmeier, Carlo Albert, Fernando Perez-Cruz; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:1039-1063
Causal Discovery for Linear Non-Gaussian Models with Disjoint Cycles
Mathias Drton, Marina Garrote-López, Niko Nikov, Elina Robeva, Y. Samuel Wang; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:1064-1083
Tuning Algorithmic and Architectural Hyperparameters in Graph-Based Semi-Supervised Learning with Provable Guarantees
Ally Yalei Du, Eric Huang, Dravyansh Sharma; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:1084-1111
Computationally Efficient Methods for Invariant Feature Selection with Sparsity
Jane Du, Arindam Banerjee; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:1112-1120
Probabilistic Semantics Guided Discovery of Approximate Functional Dependencies
Liang Duan, Xinran Wu, Xinhui Li, Lixing Yu, Kun Yue; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:1121-1134
Learning Causal Response Representations through Direct Effect Analysis
Homer Durand, Gherardo Varando, Gustau Camps-Valls; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:1135-1166
Toward Universal Laws of Outlier Propagation
Aram Ebtekar, Yuhao Wang, Dominik Janzing; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:1167-1183
Mixup Regularization: A Probabilistic Perspective
Yousef El-Laham, Niccolo Dalmasso, Svitlana Vyetrenko, Vamsi K. Potluru, Manuela Veloso; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:1184-1219
Proximal Interacting Particle Langevin Algorithms
Paula Cordero Encinar, Francesca Romana Crucinio, Omer Deniz Akyildiz; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:1220-1265
Generalised Probabilistic Modelling and Improved Uncertainty Estimation in Comparative LLM-as-a-judge
Yassir Fathullah, Mark Gales; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:1266-1288
Improved Uncertainty Quantification in Physics-Informed Neural Networks Using Error Bounds and Solution Bundles
Pablo Flores, Olga Graf, Pavlos Protopapas, Karim Pichara; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:1289-1336
Partial-Label Learning with Conformal Candidate Cleaning
Tobias Fuchs, Florian Kalinke; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:1337-1357
Order-Optimal Global Convergence for Actor-Critic with General Policy and Neural Critic Parametrization
Swetha Ganesh, Jiayu Chen, Washim Uddin Mondal, Vaneet Aggarwal; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:1358-1380
A Fast Optimization View: Reformulating Single Layer Attention in LLM Based on Tensor and SVM Trick, and Solving It in Matrix Multiplication Time
Yeqi Gao, Zhao Song, Weixin Wang, Junze Yin; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:1381-1452
Nonlinear Causal Discovery for Grouped Data
Konstantin Göbler, Tobias Windisch, Mathias Drton; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:1453-1475
Statistical Significance of Feature Importance Rankings
Jeremy Goldwasser, Giles Hooker; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:1476-1496
Optimal Zero-shot Regret Minimization for Selective Classification with Out-of-Distribution Detection
Eduardo Dadalto Câmara Gomes, Marco Romanelli; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:1497-1520
Over the Top-1: Uncertainty-Aware Cross-Modal Retrieval with CLIP
Lluis Gomez; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:1521-1532
Efficient Algorithms for Logistic Contextual Slate Bandits with Bandit Feedback
Tanmay Goyal, Gaurav Sinha; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:1533-1568
Guaranteed Prediction Sets for Functional Surrogate Models
Ander Gray, Vignesh Gopakumar, Sylvain Rousseau, Sebastien Destercke; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:1569-1585
On the Privacy Risks of Spiking Neural Networks: A Membership Inference Analysis
Junyi Guan, Abhijith Sharma, Chong Tian, Salem Lahlou; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:1586-1599
Learning Algorithms for Multiple Instance Regression
Aaryan Gupta, Rishi Saket; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:1600-1615
Contrast-CAT: Contrasting Activations for Enhanced Interpretability in Transformer-based Text Classifiers
Sungmin Han, Jeonghyun Lee, Sangkyun Lee; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:1616-1625
Conformal Prediction without Nonconformity Scores
Jonas Hanselle, Alireza Javanmardi, Tobias Florin Oberkofler, Yusuf Sale, Eyke Hüllermeier; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:1626-1639
Quantum Speedups for Bayesian Network Structure Learning
Juha Harviainen, Kseniya Rychkova, Mikko Koivisto; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:1640-1647
RCAP: Robust, Class-Aware, Probabilistic Dynamic Dataset Pruning
Atif Hassan, Swanand Khare, Jiaul H. Paik; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:1648-1662
SPvR: Structured Pruning via Ranking
Atif Hassan, Jiaul H. Paik, Swanand Khare; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:1663-1676
LoSAM: Local Search in Additive Noise Models with Mixed Mechanisms and General Noise for Global Causal Discovery
Sujai Hiremath, Promit Ghosal, Kyra Gan; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:1677-1709
Contaminated Multivariate Time-Series Anomaly Detection with Spatio-Temporal Graph Conditional Diffusion Models
Thi Kieu Khanh Ho, Narges Armanfard; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:1710-1729
Simulation-Free Differential Dynamics Through Neural Conservation Laws
Mengjian Hua, Eric Vanden-Eijnden, Ricky T. Q. Chen; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:1730-1744
Augmenting Online RL with Offline Data is All You Need: A Unified Hybrid RL Algorithm Design and Analysis
Ruiquan Huang, Donghao Li, Chengshuai Shi, Cong Shen, Jing Yang; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:1745-1767
FDR-SVM: A Federated Distributionally Robust Support Vector Machine via a Mixture of Wasserstein Balls Ambiguity Set
Michael Ibrahim, Heraldo Rozas, Nagi Gebraeel, Weijun Xie; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:1768-1793
Root Cause Analysis of Failures from Partial Causal Structures
Azam Ikram, Kenneth Lee, Shubham Agarwal, Shiv Kumar Saini, Saurabh Bagchi, Murat Kocaoglu; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:1794-1818
Lower Bounds on the Size of Markov Equivalence Classes
Erik L Jahn, Frederick Eberhardt, Leonard Schulman; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:1819-1836
Generative Uncertainty in Diffusion Models
Metod Jazbec, Eliot Wong-Toi, Guoxuan Xia, Dan Zhang, Eric Nalisnick, Stephan Mandt; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:1837-1858
Fast Calculation of Feature Contributions in Boosting Trees
Zhongli Jiang, Min Zhang, Dabao Zhang; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:1859-1875
Coevolutionary Emergent Systems Optimization with Applications to Ultra-High-Dimensional Metasurface Design : OAM Wave Manipulation
Zhengxuan Jiang, Guowen Ding, Wen Jiang; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:1876-1894
Best Possible Q-Learning
Jiechuan Jiang, Zongqing Lu; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:1895-1908
Distributional Reinforcement Learning with Dual Expectile-Quantile Regression
Sami Jullien, Romain Deffayet, Jean-Michel Renders, Paul Groth, Maarten de Rijke; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:1909-1923
Provably Adaptive Average Reward Reinforcement Learning for Metric Spaces
Avik Kar, Rahul Singh; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:1924-1964
ELF: Federated Langevin Algorithms with Primal, Dual and Bidirectional Compression
Avetik Karagulyan, Peter Richtárik; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:1965-1989
Adapting Prediction Sets to Distribution Shifts Without Labels
Kevin Kasa, Zhiyu Zhang, Heng Yang, Graham W. Taylor; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:1990-2010
Moments of Causal Effects
Yuta Kawakami, Jin Tian; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:2011-2043
Decomposition of Probabilities of Causation with Two Mediators
Yuta Kawakami, Jin Tian; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:2044-2068
Explaining Negative Classifications of AI Models in Tumor Diagnosis
David A. Kelly, Hana Chockler, Nathan Blake; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:2069-2081
Enumerating Optimal Cost-Constrained Adjustment Sets
Batya Kenig; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:2082-2100
Accurate and Scalable Stochastic Gaussian Process Regression via Learnable Coreset-based Variational Inference
Mert Ketenci, Adler J Perotte, Noémie Elhadad, Iñigo Urteaga; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:2101-2142
Efficiently Escaping Saddle Points for Policy Optimization
Mohammadsadegh Khorasani, Saber Salehkaleybar, Negar Kiyavash, Niao He, Matthias Grossglauser; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:2143-2162
Collaborative Prediction: To Join or To Disjoin Datasets
Kyung Rok Kim, Yansong Wang, Xiaocheng Li, Guanting Chen; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:2163-2201
Bayesian Optimization with Inexact Acquisition: Is Random Grid Search Sufficient?
Hwanwoo Kim, Chong Liu, Yuxin Chen; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:2202-2222
Causal Effect Identification in Heterogeneous Environments from Higher-Order Moments
Yaroslav Kivva, Sina Akbari, Saber Salehkaleybar, Negar Kiyavash; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:2223-2254
A Multivariate Unimodality Test Harnessing the Dip Statistic of Mahalanobis Distances Over Random Projections
Prodromos Kolyvakis, Aristidis Likas; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:2255-2268
DF$^2$: Distribution-Free Decision-Focused Learning
Lingkai Kong, Wenhao Mu, Jiaming Cui, Yuchen Zhuang, B. Aditya Prakash, Bo Dai, Chao Zhang; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:2269-2290
Error Bounds for Physics-Informed Neural Networks in Fokker-Planck PDEs
Chun-Wei Kong, Luca Laurenti, Jay McMahon, Morteza Lahijanian; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:2291-2324
Robust Optimization with Diffusion Models for Green Security
Lingkai Kong, Haichuan Wang, Yuqi Pan, Cheol Woo Kim, Mingxiao Song, Alayna Nguyen, Tonghan Wang, Haifeng Xu, Milind Tambe; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:2325-2344
Probabilistic Explanations for Regression Models
Frédéric Koriche, Jean-Marie Lagniez, Chi Tran; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:2345-2362
An Optimal Algorithm for Strongly Convex Min-Min Optimization
Dmitry Kovalev, Alexander Gasnikov, Grigory Malinovsky; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:2363-2379
Budget Allocation Exploiting Label Correlation between Instances
Adithya Kulkarni, Mohna Chakraborty, Sihong Xie, Qi Li; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:2380-2395
Beyond Sin-Squared Error: Linear Time Entrywise Uncertainty Quantification for Streaming PCA
Syamantak Kumar, Shourya Pandey, Purnamrita Sarkar; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:2396-2430
A Probabilistic Neuro-symbolic Layer for Algebraic Constraint Satisfaction
Leander Kurscheidt, Paolo Morettin, Roberto Sebastiani, Andrea Passerini, Antonio Vergari; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:2431-2471
Adaptive Reward Design for Reinforcement Learning
Minjae Kwon, Ingy ElSayed-Aly, Lu Feng; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:2472-2485
Constraint-based Causal Discovery from a Collection of Conditioning Sets
Kenneth Lee, Bruno Ribeiro, Murat Kocaoglu; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:2486-2516
Trading Off Voting Axioms for Privacy
Zhechen Li, Ao Liu, Lirong Xia, Yongzhi Cao, Hanpin Wang; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:2517-2536
Enhancing Uncertainty Quantification in Large Language Models through Semantic Graph Density
Zhaoye Li, Siyuan Shen, Wenjing Yang, Ruochun Jin, Huan Chen, Ligong Cao, Jing Ren; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:2537-2551
Dynamic Maintenance of Kernel Density Estimation Data Structure: From Practice to Theory
Jiehao Liang, Zhao Song, Zhaozhuo Xu, Junze Yin, Danyang Zhuo; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:2552-2581
Flat Posterior Does Matter For Bayesian Model Averaging
Sungjun Lim, Jeyoon Yeom, Sooyon Kim, Hoyoon Byun, Jinho Kang, Yohan Jung, Jiyoung Jung, Kyungwoo Song; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:2582-2617
FedSPD: A Soft-clustering Approach for Personalized Decentralized Federated Learning
I-Cheng Lin, Osman Yagan, Carlee Joe-Wong; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:2618-2641
CP$^2$: Leveraging Geometry for Conformal Prediction via Canonicalization
Putri A Van der Linden, Alexander Timans, Erik J Bekkers; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:2642-2658
Multi-group Uncertainty Quantification for Long-form Text Generation
Terrance Liu, Steven Wu; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:2659-2684
DyGMAE: A Novel Dynamic Graph Masked Autoencoder for Link Prediction
Weixiong Liu, Junwei Cheng, Zhongyu Pan, Chaobo He, Quanlong Guan; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:2685-2700
Letting Uncertainty Guide Your Multimodal Machine Translation
Wuyi Liu, Yue Gao, Yige Mao, Jing Zhao; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:2701-2710
STIMULUS: Achieving Fast Convergence and Low Sample Complexity in Stochastic Multi-Objective Learning
Zhuqing Liu, Chaosheng Dong, Michinari Momma, Simone Shao, Shaoyuan Xu, Yan Gao, Haibo Yang, Jia Liu; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:2711-2747
Periodical Moving Average Accelerates Gradient Accumulation for Post-Training
Yumou Liu, An Li, Chaojie Li, Fei Yu, Benyou Wang; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:2748-2768
Beyond Invisibility: Learning Robust Visible Watermarks for Stronger Copyright Protection
Tianci Liu, Tong Yang, Quan Zhang, Qi Lei; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:2769-2785
Guiding Time-Varying Generative Models with Natural Gradients on Exponential Family Manifold
Song Liu, Leyang Wang, Yakun Wang; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:2786-2803
Federated Rényi Fair Inference in Federated Heterogeneous System
Zhiyong Ma, Yuanjie Shi, Yan Yan, Jian Chen; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:2804-2843
Multi-armed Bandits with Missing Outcomes
Ilia Mahrooghi, Mahshad Moradi, Sina Akbari, Negar Kiyavash; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:2844-2875
Weak to Strong Learning from Aggregate Labels
Yukti Makhija, Rishi Saket; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:2876-2891
SALSA: A Secure, Adaptive and Label-Agnostic Scalable Algorithm for Machine Unlearning
Owais Makroo, Atif Hassan, Swanand Khare; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:2892-2905
Testing Generalizability in Causal Inference
Daniel de Vassimon Manela, Linying Yang, Robin J. Evans; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:2906-2927
MindFlayer SGD: Efficient Parallel SGD in the Presence of Heterogeneous and Random Worker Compute Times
Arto Maranjyan, Omar Shaikh Omar, Peter Richtárik; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:2928-2957
Off-policy Predictive Control with Causal Sensitivity Analysis
Myrl G Marmarelis, Ali Hasan, Kamyar Azizzadenesheli, R. Michael Alvarez, Anima Anandkumar; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:2958-2972
Improved Variational Inference in Discrete VAEs using Error Correcting Codes
María Martínez-García, Grace Villacrés, David Mitchell, Pablo M. Olmos; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:2973-3012
A Quantum Information Theoretic Approach to Tractable Probabilistic Models
Pedro Zuidberg Dos Martires; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:3013-3030
ODD: Overlap-aware Estimation of Model Performance under Distribution Shift
Aayush Mishra, Anqi Liu; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:3031-3047
SpinSVAR: Estimating Structural Vector Autoregression Assuming Sparse Input
Panagiotis Misiakos, Markus Püschel; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:3048-3092
When Extragradient Meets PAGE: Bridging Two Giants to Boost Variational Inequalities
Gleb Molodtsov, Valery Parfenov, Egor Petrov, Evseev Grigoriy, Daniil Medyakov, Aleksandr Beznosikov; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:3093-3122
Relational Causal Discovery with Latent Confounders
Matteo Negro, Andrea Piras, Ragib Ahsan, David Arbour, Elena Zheleva; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:3123-3154
Temperature Optimization for Bayesian Deep Learning
Kenyon Ng, Chris van der Heide, Liam Hodgkinson, Susan Wei; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:3155-3181
Multiple Wasserstein Gradient Descent Algorithm for Multi-Objective Distributional Optimization
Hai Dai Nguyen, Hiroshi Mamitsuka, Atsuyoshi Nakamura; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:3182-3199
Stochastic Embeddings : A Probabilistic and Geometric Analysis of Out-of-Distribution Behavior
Anthony Nguyen, Emanuel Aldea, Sylvie Le Hégarat-Mascle, Renaud Lustrat; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:3200-3220
Bayesian Optimization over Bounded Domains with the Beta Product Kernel
Huy Hoang Nguyen, Han Zhou, Matthew B. Blaschko, Aleksei Tiulpin; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:3221-3234
i$^2$VAE: Interest Information Augmentation with Variational Regularizers for Cross-Domain Sequential Recommendation
Xuying Ning, Wujiang Xu, Tianxin Wei, Xiaolei Liu; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:3235-3251
Discriminative ordering through ensemble consensus
Louis Ohl, Fredrik Lindsten; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:3252-3271
Do Vendi Scores Converge with Finite Samples? Truncated Vendi Score for Finite-Sample Convergence Guarantees
Azim Ospanov, Farzan Farnia; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:3272-3299
Probability-Raising Causality for Uncertain Parametric Markov Decision Processes with PAC Guarantees
Ryohei Oura, Yuji Ito; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:3300-3321
An Information-theoretic Perspective of Hierarchical Clustering on Graphs
Yicheng Pan, Bingchen Fan, Pengyu Long, Feng Zheng; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:3322-3345
Concept Forgetting via Label Annealing
Subhodip Panda, Ananda Theertha Suresh, Atri Guha, Prathosh Ap; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:3346-3360
Correlated Quantization for Faster Nonconvex Distributed Optimization
Andrei Panferov, Yury Demidovich, Ahmad Rammal, Peter Richtárik; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:3361-3387
Exploring Exploration in Bayesian Optimization
Leonard Papenmeier, Nuojin Cheng, Stephen Becker, Luigi Nardi; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:3388-3415
Probabilistic Graph Circuits: Deep Generative Models for Tractable Probabilistic Inference over Graphs
Milan Papez, Martin Rektoris, Vaclav Smidl, Tomáš Pevný; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:3416-3450
A Trust-Region Method for Graphical Stein Variational Inference
Liam Pavlovic, David M Rosen; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:3451-3464
Are You Doing Better Than Random Guessing? A Call for Using Negative Controls When Evaluating Causal Discovery Algorithms
Anne Helby Petersen; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:3465-3479
Multi-Label Bayesian Active Learning with Inter-Label Relationships
Yuanyuan Qi, Jueqing Lu, Xiaohao Yang, Joanne Enticott, Lan Du; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:3480-3491
Enhanced Equilibria-Solving via Private Information Pre-Branch Structure in Adversarial Team Games
Chen Qiu, Haobo Fu, Kai Li, Jiajia Zhang, Xuan Wang; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:3492-3506
FeDCM: Federated Learning of Deep Causal Generative Models
Md Musfiqur Rahman, Murat Kocaoglu; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:3507-3524
COS-DPO: Conditioned One-Shot Multi-Objective Fine-Tuning Framework
Yinuo Ren, Tesi Xiao, Michael Shavlovsky, Lexing Ying, Holakou Rahmanian; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:3525-3551
Learning with Confidence
Oliver Ethan Richardson; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:3552-3569
What is the Right Notion of Distance between Predict-then-Optimize Tasks?
Paula Rodriguez-Diaz, Lingkai Kong, Kai Wang, David Alvarez-Melis, Milind Tambe; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:3570-3586
Scalable Bayesian Low-Rank Adaptation of Large Language Models via Stochastic Variational Subspace Inference
Colin Samplawski, Adam D. Cobb, Manoj Acharya, Ramneet Kaur, Susmit Jha; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:3587-3604
On Information-Theoretic Measures of Predictive Uncertainty
Kajetan Schweighofer, Lukas Aichberger, Mykyta Ielanskyi, Sepp Hochreiter; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:3605-3640
Distributionally and Adversarially Robust Logistic Regression via Intersecting Wasserstein Balls
Aras Selvi, Eleonora Kreacic, Mohsen Ghassemi, Vamsi K. Potluru, Tucker Balch, Manuela Veloso; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:3641-3674
Revisiting the Equivalence of Bayesian Neural Networks and Gaussian Processes: On the Importance of Learning Activations
Marcin Sendera, Amin Sorkhei, Tomasz Kuśmierczyk; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:3675-3700
Scaling Probabilistic Circuits via Data Partitioning
Jonas Seng, Florian Peter Busch, Pooja Prasad, Devendra Singh Dhami, Martin Mundt, Kristian Kersting; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:3701-3717
Conformal Prediction Sets for Deep Generative Models via Reduction to Conformal Regression
Hooman Shahrokhi, Devjeet Raj Roy, Yan Yan, Venera Arnaoudova, Jana Doppa; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:3718-3748
Reparameterizing Hybrid Markov Logic Networks to handle Covariate-Shift in Representations
Anup Shakya, Abisha Thapa Magar, Somdeb Sarkhel, Deepak Venugopal; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:3749-3765
Divide and Orthogonalize: Efficient Continual Learning with Local Model Space Projection
Jin Shang, Simone Shao, Tian Tong, Fan Yang, Yetian Chen, Yang Jiao, Jia Liu, Yan Gao; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:3766-3786
Experimentation under Treatment Dependent Network Interference
Shiv Shankar, Ritwik Sinha, Madalina Fiterau; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:3787-3808
Learning Robust XGBoost Ensembles for Regression Tasks
Atri Vivek Sharma, Panagiotis Kouvaros, Alessio Lomuscio; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:3809-3825
Minimax Optimal Nonsmooth Nonparametric Regression via Fractional Laplacian Eigenmaps
Zhaoyang Shi, Krishna Balasubramanian, Wolfgang Polonik; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:3826-3845
Critical Influence of Overparameterization on Sharpness-aware Minimization
Sungbin Shin, Dongyeop Lee, Maksym Andriushchenko, Namhoon Lee; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:3846-3877
The Causal Information Bottleneck and Optimal Causal Variable Abstractions
Francisco N. F. Q. Simoes, Mehdi Dastani, Thijs van Ommen; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:3878-3897
Truthful Elicitation of Imprecise Forecasts
Anurag Singh, Siu Lun Chau, Krikamol Muandet; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:3898-3919
Learning from Label Proportions and Covariate-shifted Instances
Sagalpreet Singh, Navodita Sharma, Shreyas Havaldar, Rishi Saket, Aravindan Raghuveer; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:3920-3938
Approximate Bayesian Inference via Bitstring Representations
Aleksanteri Sladek, Martin Trapp, Arno Solin; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:3939-3957
Proxy-informed Bayesian transfer learning with unknown sources
Sabina J. Sloman, Julien Martinelli, Samuel Kaski; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:3958-3978
Privacy-Preserving Neural Processes for Probabilistic User Modeling
Amir Sonee, Haripriya Harikumar, Alex Hämäläinen, Lukas Prediger, Samuel Kaski; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:3979-3998
RDI: An adversarial robustness evaluation metric for deep neural networks based on model statistical features
Jialei Song, Xingquan Zuo, Feiyang Wang, Hai Huang, Tianle Zhang; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:3999-4012
Pure and Strong Nash Equilibrium Computation in Compactly Representable Aggregate Games
Jared Soundy, Mohammad T. Irfan, Hau Chan; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:4013-4033
Nonparametric Bayesian inference of item-level features in classifier combination
Patrick Stinson, Nikolaus Kriegeskorte; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:4034-4043
On Constant Regret for Low-Rank MDPs
Alexander Sturm, Sebastian Tschiatschek; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:4044-4079
Adaptive Human-Robot Collaboration using Type-Based IRL
Prasanth Sengadu Suresh, Prashant Doshi, Bikramjit Banerjee; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:4080-4091
Transparent Trade-offs between Properties of Explanations
Hiwot Belay Tadesse, Alihan Hüyük, Yaniv Yacoby, Weiwei Pan, Finale Doshi-Velez; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:4092-4112
FALCON: Adaptive Cross-Domain APT Attack Investigation with Federated Causal Learning
Jialu Tang, Yali Gao, Xiaoyong Li, Jiawei Li, Shui Yu, Binxing Fang; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:4113-4131
InfoDPCCA: Information-Theoretic Dynamic Probabilistic Canonical Correlation Analysis
Shiqin Tang, Shujian Yu; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:4132-4144
Metric Learning in an RKHS
Gokcan Tatli, Yi Chen, Blake Mason, Robert D Nowak, Ramya Korlakai Vinayak; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:4145-4164
A Unified Data Representation Learning for Non-parametric Two-sample Testing
Xunye Tian, Liuhua Peng, Zhijian Zhou, Mingming Gong, Arthur Gretton, Feng Liu; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:4165-4184
Adversarial Training May Induce Deteriorating Distributions
Runzhi Tian, Yongyi Mao; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:4185-4203
On Continuous Monitoring of Risk Violations under Unknown Shift
Alexander Timans, Rajeev Verma, Eric Nalisnick, Christian A. Naesseth; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:4204-4226
HDP-Flow: Generalizable Bayesian Nonparametric Model for Time Series State Discovery
Sana Tonekaboni, Tina Behrouzi, Addison Weatherhead, Emily Fox, David Blei, Anna Goldenberg; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:4227-4250
Optimal Transport Alignment of User Preferences from Ratings and Texts
Nhu-Thuat Tran, Hady W. Lauw; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:4251-4265
Black-box Optimization with Unknown Constraints via Overparameterized Deep Neural Networks
Dat Phan Trong, Hung The Tran, Sunil Gupta; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:4266-4289
EERO: Early Exit with Reject Option for Efficient Classification with limited budget
Florian Valade, Mohamed Hebiri, Paul Gay; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:4290-4308
Probabilistic Embeddings for Frozen Vision-Language Models: Uncertainty Quantification with Gaussian Process Latent Variable Models
Aishwarya Venkataramanan, Paul Bodesheim, Joachim Denzler; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:4309-4328
Offline Changepoint Detection With Gaussian Processes
Janneke Verbeek, Tom Heskes, Yuliya Shapovalova; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:4329-4348
Hindsight Merging: Diverse Data Generation with Language Models
Veniamin Veselovsky, Benedikt Stroebl, Gianluca Bencomo, Dilip Arumugam, Lisa Schut, Arvind Narayanan, Thomas L. Griffiths; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:4349-4369
A Trajectory-Based Bayesian Approach to Multi-Objective Hyperparameter Optimization with Epoch-Aware Trade-Offs
Wenyu Wang, Zheyi Fan, Szu Hui Ng; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:4370-4394
Targeted Learning for Variable Importance
Xiaohan Wang, Yunzhe Zhou, Giles Hooker; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:4395-4410
Nonparametric Bayesian Multi-Facet Clustering for Longitudinal Data
Luwei Wang, Kieran Richards, Sohan Seth; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:4411-4442
A Parallel Network for LRCT Segmentation and Uncertainty Mitigation with Fuzzy Sets
Shiyi Wang, Yang Nan, Xiaodan Xing, Yingying Fang, Simon Lf Walsh, Guang Yang; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:4443-4457
VADIS: Investigating Inter-View Representation Biases for Multi-View Partial Multi-Label Learning
Jie Wang, Ning Xu, Xin Geng; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:4458-4471
MutualNeRF: Improve the Performance of NeRF under Limited Samples with Mutual Information Theory
Zifan Wang, Jingwei Li, Yitang Li, Yunze Liu; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:4472-4488
Informative Synthetic Data Generation for Thorax Disease Classification
Yancheng Wang, Rajeev Goel, Marko Jojic, Alvin C. Silva, Teresa Wu, Yingzhen Yang; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:4489-4514
A Mirror Descent Perspective of Smoothed Sign Descent
Shuyang Wang, Diego Klabjan; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:4515-4542
Geodesic Slice Sampler for Multimodal Distributions with Strong Curvature
Bernardo Williams, Hanlin Yu, Hoang Phuc Hau Luu, Georgios Arvanitidis, Arto Klami; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:4543-4564
Online Generalized Magician’s Problem with Multiple Workers
Ruoyu Wu, Wei Bao, Ben Liang, Liming Ge; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:4565-4596
Group-Agent Reinforcement Learning with Heterogeneous Agents
Kaiyue Wu, Xiao-Jun Zeng, Tingting Mu; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:4597-4617
FlightPatchNet: Multi-Scale Patch Network with Differential Coding for Short-Term Flight Trajectory Prediction
Lan Wu, Xuebin Wang, Ruijuan Chu, Guangyi Liu, Jing Zhang, Linyu Wang; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:4618-4635
The Consistency Hypothesis in Uncertainty Quantification for Large Language Models
Quan Xiao, Debarun Bhattacharjya, Balaji Ganesan, Radu Marinescu, Katya Mirylenka, Nhan H Pham, Michael Glass, Junkyu Lee; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:4636-4651
Learning Multi-interest Embedding with Dynamic Graph Cluster for Sequention Recommendation
Xiao Chunjing, Ranhao Guo, Zhang Yongwang, Xiaoming Wu; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:4652-4662
Variational Learning of Gaussian Process Latent Variable Models through Stochastic Gradient Annealed Importance Sampling
Jian Xu, Shian Du, Junmei Yang, Qianli Ma, Delu Zeng, John Paisley; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:4663-4680
Dependent Randomized Rounding for Budget Constrained Experimental Design
Khurram Yamin, Edward Kennedy, Bryan Wilder; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:4681-4700
Full Network Capacity Framework for Sample-Efficient Deep Reinforcement Learning
Wentao Yang, Xinyue Liu, Yunlong Gao, Wenxin Liang, Linlin Zong, Guanglu Wang, Xianchao Zhang; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:4701-4714
Best Arm Identification with Possibly Biased Offline Data
Le Yang, Vincent Y. F. Tan, Wang Chi Cheung; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:4715-4730
MSCGrapher: Learning Multi-Scale Dynamic Correlations for Multivariate Time Series Forecasting
Xian Yang, Zhenguo Zhang, Shihao Lu; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:4731-4751
Flow-Based Delayed Hawkes Process
Chao Yang, Wendi Ren, Shuang Li; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:4752-4774
$σ$-Maximal Ancestral Graphs
Binghua Yao, Joris Marten Mooij; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:4775-4805
How Likely Are Two Voting Rules Different?
Ziqi Yu, Lirong Xia, Qishen Han, Chengkai Zhang; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:4806-4825
Corruption-Robust Variance-aware Algorithms for Generalized Linear Bandits under Heavy-tailed Rewards
Qingyuan Yu, Euijin Baek, Xiang Li, Qiang Sun; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:4826-4843
Complete Characterization for Adjustment in Summary Causal Graphs of Time Series
Clément Yvernes, Emilie Devijver, Eric Gaussier; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:4844-4871
Label Distribution Learning using the Squared Neural Family on the Probability Simplex
Daokun Zhang, Russell Tsuchida, Dino Sejdinovic; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:4872-4888
Learning to Stabilize Unknown LTI Systems on a Single Trajectory under Stochastic Noise
Ziyi Zhang, yorie nakahira, Guannan Qu; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:4889-4919
Instance-Wise Monotonic Calibration by Constrained Transformation
Yunrui Zhang, Gustavo Enrique Batista, Salil S. Kanhere; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:4920-4932
Causal Eligibility Traces for Confounding Robust Off-Policy Evaluation
Junzhe Zhang, Elias Bareinboim; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:4933-4942
Improving Adversarial Transferability via Decision Boundary Adaptation
Jiayu Zhang, Zhiyu Zhu, Zhibo Jin, Xinyi Wang, Huaming Chen, Kim-Kwang Raymond Choo; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:4943-4958
Near-Optimal Regret Bounds for Federated Multi-armed Bandits with Fully Distributed Communication
Haoran Zhang, Xuchuang Wang, Hao-Xu Chen, Hao Qiu, Lin Yang, Yang Gao; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:4959-4981
Residual Reweighted Conformal Prediction for Graph Neural Networks
Zheng Zhang, Jie Bao, Zhixin Zhou, nicolo colombo, Lixin Cheng, Rui Luo; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:4982-4999
Finding Interior Optimum of Black-box Constrained Objective with Bayesian Optimization
Fengxue Zhang, Yuxin Chen; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:5000-5029
Sample and Computationally Efficient Continuous-Time Reinforcement Learning with General Function Approximation
Runze Zhao, Yue Yu, Adams Yiyue Zhu, Chen Yang, Dongruo Zhou; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:5030-5057
Towards Provably Efficient Learning of Imperfect Information Extensive-Form Games with Linear Function Approximation
Canzhe Zhao, Shuze Chen, Weiming Liu, Haobo Fu, Qiang Fu, Shuai Li; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:5058-5083
Collapsing Sequence-Level Data-Policy Coverage via Poisoning Attack in Offline Reinforcement Learning
Xue Zhou, Dapeng Man, Chen Xu, Fanyi Zeng, Tao Liu, Huan Wang, Shucheng He, Chaoyang Gao, Wu Yang; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:5084-5098
Learning to Sample in Stochastic Optimization
Sijia Zhou, Yunwen Lei, Ata Kaban; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:5099-5115
MSP-SR: Multi-Stage Probabilistic Generative Super Resolution with Scarce High-Resolution Data
Ruike Zhu, Matthew Charles Weston, Hanwen Zhang, Arindam Banerjee; Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence, PMLR 286:5116-5134
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