Search Results for author:
Found 6 papers, 1 papers with code
Ensemble Successor Representations for Task Generalization in Offline-to-Online Reinforcement Learning
To address this problem, our work builds upon the investigation of successor representations for task generalization in online RL and extends the framework to incorporate offline-to-online learning.
Contrastive Representation for Data Filtering in Cross-Domain Offline Reinforcement Learning
In this paper, we propose a novel representation-based approach to measure the domain gap, where the representation is learned through a contrastive objective by sampling transitions from different domains.
Diverse Randomized Value Functions: A Provably Pessimistic Approach for Offline Reinforcement Learning
Offline Reinforcement Learning (RL) faces distributional shift and unreliable value estimation, especially for out-of-distribution (OOD) actions.
Regularized Conditional Diffusion Model for Multi-Task Preference Alignment
Sequential decision-making is desired to align with human intents and exhibit versatility across various tasks.
Towards Robust Offline-to-Online Reinforcement Learning via Uncertainty and Smoothness
Experimental results illustrate the superiority of RO2O in facilitating stable offline-to-online learning and achieving significant improvement with limited online interactions.
6 GHz hyperfast rotation of an optically levitated nanoparticle in vacuum
We measure a highest rotation frequency about 4. 3 GHz of the trapped nanoparticle without feedback cooling and a 6 GHz rotation with feedback cooling, which is the fastest mechanical rotation ever reported to date.
Optics Mesoscale and Nanoscale Physics Quantum Physics
