19 citations · 150 across the 48 of their papers we have counts for
5 papers · 1 filter
Uncertainty-aware Low-Rank Q-Matrix Estimation for Deep Reinforcement Learning
Tong Sang, Hongyao Tang, Jianye Hao +2
Value estimation is one key problem in Reinforcement Learning. Albeit many successes have been achieved by Deep Reinforcement Learning (DRL) in different fields, the underlying str…
SEIHAI: A Sample-efficient Hierarchical AI for the MineRL Competition
Hangyu Mao, Chao Wang, Xiaotian Hao +6
The MineRL competition is designed for the development of reinforcement learning and imitation learning algorithms that can efficiently leverage human demonstrations to drastically…
Ranking Cost: Building An Efficient and Scalable Circuit Routing Planner with Evolution-Based Optimization
Shiyu Huang, Bin Wang, Dong Li +3
Circuit routing has been a historically challenging problem in designing electronic systems such as very large-scale integration (VLSI) and printed circuit boards (PCBs). The main…
HyAR: Addressing Discrete-Continuous Action Reinforcement Learning via Hybrid Action Representation
Boyan Li, Hongyao Tang, Yan Zheng +5
Discrete-continuous hybrid action space is a natural setting in many practical problems, such as robot control and game AI. However, most previous Reinforcement Learning (RL) works…
Modeling Scale-free Graphs with Hyperbolic Geometry for Knowledge-aware Recommendation
Yankai Chen, Menglin Yang, Yingxue Zhang +4
Aiming to alleviate data sparsity and cold-start problems of traditional recommender systems, incorporating knowledge graphs (KGs) to supplement auxiliary information has recently…