Papers
Time-aware Motion Planning in Dynamic Environments with Conformal Prediction
Kaier Liang, Licheng Luo, Yixuan Wang et al.
CableRobotGraphSim: A Graph Neural Network for Modeling Partially Observable Cable-Driven Robot Dynamics
Nelson Chen, William R. Johnson III, Rebecca Kramer-Bottiglio et al.
How to Train Your Latent Control Barrier Function: Smooth Safety Filtering Under Hard-to-Model Constraints
Kensuke Nakamura, Arun L Bishop, Steven Man et al.
Adapting World Models with Latent-State Dynamics Residuals
JB Lanier, Kyungmin Kim, Armin Karamzade et al.
Model-Based Reinforcement Learning under Random Observation Delays
Armin Karamzade, Kyungmin Kim, JB Lanier et al.
Scalable Data-Driven Reachability Analysis and Control via Koopman Operators with Conformal Coverage Guarantees
Devesh Nath, Haoran Yin, Glen Chou
Flickering Multi-Armed Bandits
Sourav Chakraborty, Amit Kiran Rege, Claire Monteleoni et al.
Conference on Learning Theory 2026: Preface
Steve Hanneke, Tor Lattimore
Invited Open Problem: Does Differential Privacy Make PAC Learning Much Harder?
Kobbi Nissim, Uri Stemmer, Eliad Tsfadia
Open Problem: Is Interaction Necessary for Order-Optimal 1-bit Mean Estimation?
Ivan Lau, Jonathan Scarlett
Invited Open Problem: Is the Power of Deep Learning over Linear Models Inherently Distribution Dependent?
Vitaly Feldman, Pritish Kamath, Nathan Srebro
Invited Open Problem: Online Optimization of Piecewise-Lipschitz Functions with Applications to Data-Driven Algorithm Design
Maria-Florina Balcan, Wesley Pegden, Dravyansh Sharma
Open Problem: How much overparametrization is needed for ALS in tensor decomposition?
Dionysis Arvanitakis, Vaidehi Srinivas, Aravindan Vijayaraghavan
Gradient-Variation Regret Bounds for Unconstrained Online Learning
Yuheng Zhao, Andrew Jacobsen, Nicolò Cesa-Bianchi et al.
Optimal Variance-Dependent Regret Bounds for Infinite-Horizon MDPs
Guy Zamir, Matthew Zurek, Yudong Chen
Distribution-Free Sequential Prediction with Abstentions
Jialin Yu, Moïse Blanchard
Learning Decision-Sufficient Representations for Linear Optimization
Yuhan Ye, Saurabh Amin, Asuman Özdağlar
Tight Sample Complexity of Transformers
Chenxiao Yang, Nathan Srebro, Zhiyuan Li
Optimism Stabilizes Thompson Sampling for Adaptive Inference
Shunxing Yan, Han Zhong
Worst-case Error Bounds for Online Learning of Smooth Functions
Weian (Andrew) Xie
Lyapunov-Based Sample Complexity Analysis for Weakly-Coupled MDPs (extended abstract)
Wu Tianhao, Matthew Zurek, Weina Wang et al.
Risk Comparisons in Linear Regression: Implicit Regularization Dominates Explicit Regularization (Extended Abstract)
Jingfeng Wu, Peter L. Bartlett, Sham M. Kakade et al.
Minimax Limits of k-Fold Cross-Validation via Majority
Ido Nachum, Ruediger Urbanke, Thomas Weinberger