291 citations · 439 across the 7 of their papers we have counts for
Showing 2017Show all
2 papers · 1 filter
cs.RO2017★ 10 cited
Map-based Multi-Policy Reinforcement Learning: Enhancing Adaptability of Robots by Deep Reinforcement Learning
Ayaka Kume, Eiichi Matsumoto, Kuniyuki Takahashi +2
In order for robots to perform mission-critical tasks, it is essential that they are able to quickly adapt to changes in their environment as well as to injuries and or other bodil…
stat.ML2017★ 291 cited
Learning Discrete Representations via Information Maximizing Self-Augmented Training
Weihua Hu, Takeru Miyato, Seiya Tokui +2
Learning discrete representations of data is a central machine learning task because of the compactness of the representations and ease of interpretation. The task includes cluster…