2 citations · 2 across the 3 of their papers we have counts for
3 papers
cs.LG2023
Few-Shot Image-to-Semantics Translation for Policy Transfer in Reinforcement Learning
Rei Sato, Kazuto Fukuchi, Jun Sakuma +1
We investigate policy transfer using image-to-semantics translation to mitigate learning difficulties in vision-based robotics control agents. This problem assumes two environments…
cs.LG2022★ 2 cited
Max-Min Off-Policy Actor-Critic Method Focusing on Worst-Case Robustness to Model Misspecification
Takumi Tanabe, Rei Sato, Kazuto Fukuchi +2
In the field of reinforcement learning, because of the high cost and risk of policy training in the real world, policies are trained in a simulation environment and transferred to…
cs.LG2020
AdvantageNAS: Efficient Neural Architecture Search with Credit Assignment
Rei Sato, Jun Sakuma, Youhei Akimoto
Neural architecture search (NAS) is an approach for automatically designing a neural network architecture without human effort or expert knowledge. However, the high computational…