UAI 2025

229 papers

Adaptive Threshold Sampling for Pure Exploration in Submodular Bandits

Wenjing Chen, Shuo Xing, Victoria G. Crawford

Just Trial Once: Ongoing Causal Validation of Machine Learning Models

Jacob M. Chen, Michael Oberst

Improving Graph Contrastive Learning with Community Structure

Xiang Chen, Kun Yue, Liang Duan, Lixing Yu

Unsupervised Attributed Dynamic Network Embedding with Stability Guarantees

Emma Ceccherini, Ian Gallagher, Andrew Jones, Daniel John Lawson

Out-of-distribution Robust Optimization

Zhongze Cai, Hansheng Jiang, Xiaocheng Li

Fast Non-convex Matrix Sensing with Optimal Sample Complexity

Jian-Feng CAI, Tong Wu, Ruizhe Xia

Creative Agents: Empowering Agents with Imagination for Creative Tasks

Penglin Cai, Chi Zhang, Yuhui Fu, Haoqi Yuan, Zongqing Lu

Epistemic Uncertainty in Conformal Scores: A Unified Approach

Luben Miguel Cruz Cabezas, Vagner Silva Santos, Thiago Ramos, Rafael Izbicki

Causal Models for Growing Networks

Gecia Bravo-Hermsdorff, Kayvan Sadeghi, Lee M. Gunderson

Stein Variational Evolution Strategies

Cornelius V. Braun, Robert Tjarko Lange, Marc Toussaint

Using Submodular Optimization to Approximate Minimum-Size Abductive Path Explanations for Tree-Based Models

Louènas Bounia

Multi-Cost-Bounded Reachability Analysis of POMDPs

Alexander Bork, Joost-Pieter Katoen, Tim Quatmann, Svenja Stein

BELIEF - Bayesian Sign Entropy Regularization for LIME Framework

Revoti Prasad Bora, Philipp Terhorst, Raymond Veldhuis, Raghavendra Ramachandra, Kiran Raja

Asymptotically Optimal Linear Best Feasible Arm Identification with Fixed Budget

Jie Bian, Vincent Y. F. Tan

Revisiting the Berkeley Admissions data: Statistical Tests for Causal Hypotheses

Sourbh Bhadane, Joris Marten Mooij, Philip Boeken, Onno Zoeter

Can a Bayesian Oracle Prevent Harm from an Agent?

Yoshua Bengio, Michael K. Cohen, Nikolay Malkin, Matt MacDermott, Damiano Fornasiere

Limit-sure Reachability for Small Memory Policies in POMDPs is NP-complete

Ali Asadi, Krishnendu Chatterjee, Raimundo Saona, Ali Shafiee

Lower Bound on Howard Policy Iteration for Deterministic Markov Decision Processes

Ali Asadi, Krishnendu Chatterjee, Jakob de Raaij

Hybrid Bernstein Normalizing Flows for Flexible Multivariate Density Regression with Interpretable Marginals

Marcel Arpogaus, Thomas Kneib, Thomas Nagler, David Rügamer

Evasion Attacks Against Bayesian Predictive Models

Pablo G. Arce, Roi Naveiro, David Rios Insua

Expert-In-The-Loop Causal Discovery: Iterative Model Refinement Using Expert Knowledge

Ankur Ankan, Johannes Textor

MOHITO: Multi-Agent Reinforcement Learning using Hypergraphs for Task-Open Systems

Gayathri Anil, Prashant Doshi, Daniel Alan Redder, Adam Eck, Leen-Kiat Soh

Symbiotic Local Search for Small Decision Tree Policies in MDPs

Roman Andriushchenko, Milan Ceska, Debraj Chakraborty, Sebastian Junges, Jan Křetínský

Sparse Structure Exploration and Re-optimization for Vision Transformer

Sangho An, Jinwoo Kim, Keonho Lee, Jingang Huh, Chanwoong Kwak

Conditional Average Treatment Effect Estimation Under Hidden Confounders

Ahmed Aloui, Juncheng Dong, Ali Hasan, Vahid Tarokh

CATE Estimation With Potential Outcome Imputation From Local Regression

Ahmed Aloui, Juncheng Dong, Cat Phuoc Le, Vahid Tarokh

Conformal Prediction for Federated Graph Neural Networks with Missing Neighbor Information

Ömer Faruk Akgül, Rajgopal Kannan, Viktor Prasanna

Causal Inference amid Missingness-Specific Independences and Mechanism Shifts

Johan de Aguas, Leonard Henckel, Johan Pensar, Guido Biele

Aggregating Data for Optimal Learning

Sushant Agarwal, Yukti Makhija, Rishi Saket, Aravindan Raghuveer