Hello, I am Kazuki Ota. At ICML 2026, I will present two papers: one on stable and efficient self-play reinforcement learning for two-player games at the main conference, and one on self-supervised theorem discovery from axioms alone at the AI for Math Workshop.
ICML 2026 Main Conference Paper
Jul 8, 2:30 PM-4:15 PM, Hall A #306
We revisit regularized policy optimization for two-player games and develop KLENT, a search-free self-play reinforcement learning method that improves training stability and efficiency.
project page | paper | poster | event page on web | event page on mobile
Self-Supervised Theorem Discovery in a Formal Axiomatic System
3rd AI for Math Workshop
Jul 11, 10:55 AM-12:10 PM, Hall D1
We study whether useful mathematical knowledge can emerge from axioms alone by training an agent to discover formal theorems and reuse them as lemmas for future reasoning.
I am especially interested in discussing how learning systems can search for, test, and organize new knowledge beyond direct human supervision.
If you would like to chat during ICML 2026, please contact me on LinkedIn or email me. I am happy to talk about the papers above, related research ideas, or possible collaborations.