19 citations · 150 across the 48 of their papers we have counts for
3 papers · 1 filter
HEBO Pushing The Limits of Sample-Efficient Hyperparameter Optimisation
Alexander I. Cowen-Rivers, Wenlong Lyu, Rasul Tutunov +8
In this work we rigorously analyse assumptions inherent to black-box optimisation hyper-parameter tuning tasks. Our results on the Bayesmark benchmark indicate that heteroscedastic…
What About Inputing Policy in Value Function: Policy Representation and Policy-extended Value Function Approximator
Hongyao Tang, Zhaopeng Meng, Jianye Hao +9
We study Policy-extended Value Function Approximator (PeVFA) in Reinforcement Learning (RL), which extends conventional value function approximator (VFA) to take as input not only…
An Efficient Transfer Learning Framework for Multiagent Reinforcement Learning
Tianpei Yang, Weixun Wang, Hongyao Tang +9
Transfer Learning has shown great potential to enhance single-agent Reinforcement Learning (RL) efficiency. Similarly, Multiagent RL (MARL) can also be accelerated if agents can sh…