Seminars relevant to Informatics

[Michael Gutmann <michael.gutmann AT ed.ac.uk>]

Dear all,

Please save the date for a talk by Masashi Sugiyama on Tue Sept 29, 11am 
to noon in G.07 (Informatics Forum). Please see below for the talk 
information.

Best wishes

Michael

-------------
Speaker:
Masashi Sugiyama (RIKEN/The University of Tokyo)
https://eur02.safelinks.protection.outlook.com/?url=https%3A%2F%2Fwww.ms.k.u-tokyo.ac.jp%2Fsugi%2F&data=05%7C02%7C%7C3c8887c83a454f94704908df0f528403%7C2e9f06b016694589878910a06934dc61%7C0%7C0%7C639246519196987268%7CUnknown%7CTWFpbGZsb3d8eyJFbXB0eU1hcGkiOnRydWUsIlYiOiIwLjAuMDAwMCIsIlAiOiJXaW4zMiIsIkFOIjoiTWFpbCIsIldUIjoyfQ%3D%3D%7C0%7C%7C%7C&sdata=wsd1Fu9x0%2FYNfFUM8Xg8armbjprq6PjLqg7P9poga8k%3D&reserved=0

Title:
Recent Advances in Reward Modeling for Reinforcement Learning

Abstract:
Reinforcement learning (RL) has achieved remarkable success in robotics, 
games, and language model post-training, where reward signals are 
essential for effective agent training. In this talk, I will present our 
recent research on advanced reward modeling. This includes robustifying 
RL through transfer and weakly supervised
learning, coping with interval-based rewards, and exploring diverse 
reward aggregation frameworks that move beyond the traditional 
discounted sum.

Bio:
Masashi Sugiyama received his Ph.D. in Computer Science from the Tokyo 
Institute of Technology, Japan, in 2001. After serving as an assistant 
and associate professor at the same institute, he became a professor at 
the University of Tokyo in 2014. Since 2016, he has also served as the 
director of the RIKEN Center for Advanced Intelligence Project. His 
research interests include theories and algorithms of machine learning, 
such as weakly supervised learning, distribution shift adaptation, and 
reinforcement learning. He was a keynote speaker at ICLR 2023, and is 
currently an ICML board member and a NeurIPS advisory board member.