Papers
Stochastic Dominance Driven First-Order Policy Optimization for Multi-Objective Reinforcement Learning
Ege Can Kaya, Kadierdan Kaheman, Jason M Cloud et al.
General Bayesian Policy Learning
Masahiro Kato
Likelihood hacking in probabilistic program synthesis
Jacek Karwowski, Younesse Kaddar, Zihuiwen Ye et al.
COBALT: Censored Optimization and Bayesian Active Learning Techniques
Andrea Karlova, Rishabh Kabra, Daniel Augusto de Souza et al.
Information-Theoretic Bayesian Optimization for Bilevel Optimization Problems
Takuya Kanayama, Yuki Ito, Tomoyuki Tamura et al.
Who Guards the Guardians? The Challenges of Evaluating Identifiability of Learned Representations
Shruti Joshi, Théo Saulus, Wieland Brendel et al.
PRISM: Calibrated Bayesian Fusion and Auditable Attribution for Reliable LLM Event Prediction from Text
Chengyuan Jin, Daojian Zeng, Kang Liu et al.
Improving the Convergence of Private Shuffled Gradient Methods with Public Data
Shuli Jiang, Pranay Sharma, Zhiwei Steven Wu et al.
Calibration-Aware Online Adaptation under Label Shift
Jiun Jeong, Byeongwoo An, Gi-Soo Kim et al.
Optimal Conformal Prediction under Epistemic Uncertainty
Alireza Javanmardi, Soroush H. Zargarbashi, Santo M. A. R. Thies et al.
Graph-Dependent Regret Bounds in Multi-Armed Bandits with Interference
Fateme Jamshidi, Mohammad Shahverdikondori, Negar Kiyavash
Byzantine-Robust and Differentially Private Federated Optimization under Weaker Assumptions
Rustem Islamov, Grigory Malinovsky, Alexander Gaponov et al.
Achieving Alignment Through Adaptive Play: Helping Optimize Objectives Without Observing Them
Jason T. Isa, Samuel Burden, Lillian J. Ratliff
Probabilistic Edge Modulation for High-Dimensional Causal Discovery
Seyong Hwang, Kyoungjae Lee, Sunmin Oh et al.
Balancing Expressivity and Learnability in Quantum Kernel Bandit Optimization
Yuqi Huang, Vincent Y. F. Tan, Sharu Theresa Jose
Model-Agnostic Online Certificate-Driven Calibration for Time Series Forecasting Under Distribution Shift
Chenfeng Huang, Zixuan Ma, George Michailidis
From Global to Factor-Wise Expert Composition in Discrete Diffusion Models
Haozhe Huang, Yudong Xu, Abhijoy Mandal et al.
Policy-Based Trajectory Clustering in Offline Reinforcement Learning
Xinqi Wang, Simon Shaolei Du, Hao Hu
From Bayes’ Rule to Bayes Rules: Information Processing, Bayes’ Theorem, and Imprecise Probabilities
Jeremie Houssineau, Badr-Eddine Chérief-Abdellatif
Generalized Distribution-Free Semi-Supervised Learning with Risk Rewrite
Yushi Hirose, Hiroo Irobe, Takafumi Kanamori
Identifying Labeling Mechanism in Positive–Unlabeled Learning under Unknown Class Prior
Siying He, Weijuan Liang, Jiatong Liu
Identification and Bounding of Central Moments of Causal Effects Using Marginal Moments Information
Naoya Hashimoto, Yuta Kawakami, Jin Tian