Center for Advanced Intelligence Project

Four papers have been accepted at the 38th Annual Conference on Learning Theory (COLT 2025), which will be held from June 30 to July 4, 2025 in Lyon, France.

For more details, please refer to the link below.

[Website] https://learningtheory.org/colt2025/

• Corrupted Learning Dynamics in Games.
  Taira Tsuchiya (The University of Tokyo / RIKEN AIP)
  Shinji Ito (The University of Tokyo / RIKEN AIP)
  Haipeng Luo (University of Southern California)

• Data-dependent Bounds with T-Optimal Best-of-Both-Worlds Guarantees in Multi-Armed Bandits using Stability-Penalty Matching.
  Quan Nguyen* (University of Victoria)
  Shinji Ito (The University of Tokyo / RIKEN AIP)
  Junpei Komiyama (New York University)
  Nishant A. Mehta (University of Victoria)
  * The work was done when he was an intern at RIKEN AIP.
• Instance-Dependent Regret Bounds for Learning Two-Player Zero-Sum Games with Bandit Feedback.
  Shinji Ito (The University of Tokyo / RIKEN AIP)
  Haipeng Luo (University of Southern California)
  Taira Tsuchiya (The University of Tokyo / RIKEN AIP)
  Yue Wu (University of Southern California)
• The Adaptive Complexity of Finding a Stationary Point
  Huanjian Zhou (The University of Tokyo / RIKEN AIP)
  Andi Han (RIKEN AIP)
  Akiko Takeda (The University of Tokyo / RIKEN AIP)
  Masashi Sugiyama (RIKEN AIP / The University of Tokyo)

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