all AI news
Cross-domain Random Pre-training with Prototypes for Reinforcement Learning
March 18, 2024, 4:42 a.m. | Xin Liu, Yaran Chen, Haoran Li, Boyu Li, Dongbin Zhao
cs.LG updates on arXiv.org arxiv.org
Abstract: This work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessible. Task-agnostic cross-domain pre-training shows great potential in image-based Reinforcement Learning (RL) but poses a big challenge. In this paper, we propose CRPTpro, a Cross-domain self-supervised Random Pre-Training framework with prototypes for image-based RL. CRPTpro employs cross-domain random policy to easily and quickly sample diverse data from multiple domains, to …
arxiv cs.ai cs.lg domain pre-training random reinforcement reinforcement learning training type
More from arxiv.org / cs.LG updates on arXiv.org
Digital Over-the-Air Federated Learning in Multi-Antenna Systems
2 days, 11 hours ago |
arxiv.org
Bagging Provides Assumption-free Stability
2 days, 11 hours ago |
arxiv.org
Jobs in AI, ML, Big Data
Data Architect
@ University of Texas at Austin | Austin, TX
Data ETL Engineer
@ University of Texas at Austin | Austin, TX
Lead GNSS Data Scientist
@ Lurra Systems | Melbourne
Senior Machine Learning Engineer (MLOps)
@ Promaton | Remote, Europe
Research Scientist, Demography and Survey Science, University Grad
@ Meta | Menlo Park, CA | New York City
Computer Vision Engineer, XR
@ Meta | Burlingame, CA