Showing 1–20 of 24 results
/ Date/ Name
Jun 23, 2005Acceleration Operators in the Value Iteration Algorithms for Markov Decision ProcessesAug 3, 2022Quantum-Inspired Tensor Neural Networks for Partial Differential EquationsApr 26, 2022Meta-free few-shot learning via representation learning with weight averagingAug 19, 2024Algorithmic Contract Design with Reinforcement Learning AgentsOct 14, 2024Burning RED: Unlocking Subtask-Driven Reinforcement Learning and Risk-Awareness in Average-Reward Markov Decision ProcessesFeb 29, 2020Contextual Policy Transfer in Reinforcement Learning Domains via Deep Mixtures-of-ExpertsOct 7, 2022Unsupervised Few-shot Learning via Deep Laplacian EigenmapsMar 26, 2025A Causal Perspective of Stock Prediction ModelsJun 3, 2025A Differential Perspective on Distributional Reinforcement LearningJun 10, 2020Bayesian Experience Reuse for Learning from Multiple DemonstratorsJul 2, 2020ε-BMC: A Bayesian Ensemble Approach to Epsilon-Greedy Exploration in Model-Free Reinforcement LearningJul 6, 2022Don't overfit the history -- Recursive time series data augmentationJul 28, 2025A Contrastive Diffusion-based Network (CDNet) for Time Series ClassificationSep 23, 2025Score the Steps, Not Just the Goal: VLM-Based Subgoal Evaluation for Robotic ManipulationMar 23, 2026Deep Reinforcement Learning and The Tale of Two Temporal Difference ErrorsDec 11, 2012The Bayesian process control with multiple assignable causesFeb 18, 2025Hypernetwork-based approach for optimal composition design in partially controlled multi-agent systemsAug 21, 2024Bayesian Optimization Framework for Efficient Fleet Design in Autonomous Multi-Robot ExplorationOct 3, 2025Ergodic Risk Measures: Towards a Risk-Aware Foundation for Continual Reinforcement LearningMay 28, 2021Risk-Aware Transfer in Reinforcement Learning using Successor Features