This theme studies algorithms that learn from feedback obtained through online decision making. I focus on achieving stable learning under partial feedback and in environments that change over time.
Key questions
#- How can agents learn efficiently from partial feedback?
- How can stable learning be achieved in environments that change over time?
Related Publications
AAMAS 2026 (Extended abstract)
Yuma Fujimoto, Kaito Ariu, Kenshi Abe
Theme:Bandits & Online LearningWSDM 2025 (Industry day talks)
Daiki Katsuragawa, Yusuke Kaneko, Kaito Ariu, Kenshi Abe
Theme:Bandits & Online LearningSIGIR 2023 (Short Paper)
Hiroaki Shiino, Kaito Ariu, Kenshi Abe, Togashi Riku
Theme:Bandits & Online LearningICML 2022
Kaito Ariu, Kenshi Abe, Alexandre Proutière
Theme:Bandits & Online LearningarXiv
Masahiro Kato, Kenshi Abe, Kaito Ariu, Shota Yasui
Theme:Bandits & Online LearningAAAI 2020 Workshop on Reinforcement Learning in Games
Gota Morishita, Kenshi Abe, Kazuhisa Ogawa, Yusuke Kaneko
Theme:Bandits & Online Learning