Oral "reinforcement learning" Papers
19 papers found
Conference
Conformal Prediction Beyond the Horizon: Distribution-Free Inference for Policy Evaluation
Feichen Gan, Lu Youcun, Yingying Zhang et al.
Dynamic Contrastive Skill Learning with State-Transition Based Skill Clustering and Dynamic Length Adjustment
Jinwoo Choi, Seung-Woo Seo
EvoLM: In Search of Lost Language Model Training Dynamics
Zhenting Qi, Fan Nie, Alexandre Alahi et al.
Heterogeneous Graph Transformers for Simultaneous Mobile Multi-Robot Task Allocation and Scheduling under Temporal Constraints
Batuhan Altundas, Shengkang Chen, Shivika Singh et al.
Learning to Reuse Policies in State Evolvable Environments
Ziqian Zhang, Bohan Yang, Lihe Li et al.
Meta-learning how to Share Credit among Macro-Actions
Ionel-Alexandru Hosu, Traian Rebedea, Razvan Pascanu
No-Regret Thompson Sampling for Finite-Horizon Markov Decision Processes with Gaussian Processes
Jasmine Bayrooti, Sattar Vakili, Amanda Prorok et al.
Omni-R1: Reinforcement Learning for Omnimodal Reasoning via Two-System Collaboration
Hao Zhong, Muzhi Zhu, Zongze Du et al.
Periodic Skill Discovery
Jonghae Park, Daesol Cho, Jusuk Lee et al.
Semantic Temporal Abstraction via Vision-Language Model Guidance for Efficient Reinforcement Learning
Tian-Shuo Liu, Xu-Hui Liu, Ruifeng Chen et al.
Temporal Difference Learning: Why It Can Be Fast and How It Will Be Faster
Patrick Schnell, Luca Guastoni, Nils Thuerey
The ODE Method for Stochastic Approximation and Reinforcement Learning with Markovian Noise
Shuze Daniel Liu, Shuhang Chen, Shangtong Zhang
Time-R1: Post-Training Large Vision Language Model for Temporal Video Grounding
Ye Wang, Ziheng Wang, Boshen Xu et al.
VideoChat-R1.5: Visual Test-Time Scaling to Reinforce Multimodal Reasoning by Iterative Perception
Ziang Yan, Yinan He, Xinhao Li et al.
An Improved Finite-time Analysis of Temporal Difference Learning with Deep Neural Networks
Zhifa Ke, Zaiwen Wen, Junyu Zhang
Learning Temporal Distances: Contrastive Successor Features Can Provide a Metric Structure for Decision-Making
Vivek Myers, Chongyi Zheng, Anca Dragan et al.
Reinforcement Learning from Reachability Specifications: PAC Guarantees with Expected Conditional Distance
Jakub Svoboda, Suguman Bansal, Krishnendu Chatterjee
Value-Evolutionary-Based Reinforcement Learning
Pengyi Li, Jianye Hao, Hongyao Tang et al.
When Do Skills Help Reinforcement Learning? A Theoretical Analysis of Temporal Abstractions
Zhening Li, Gabriel Poesia, Armando Solar-Lezama