Center for Advanced Intelligence Project

Three papers have been accepted at the Annual Conference on Learning Theory (COLT) 2024.

For more details, please refer to the link below.

[Website] https://learningtheory.org/colt2024/

• COLT2024
  June 30–July 3, 2024 in Edmonton, Canada.
• Adaptive Learning Rate for Follow-the-Regularized-Leader: Competitive Ratio Analysis and Best-of-Both-Worlds
  Shinji Ito (The University of Tokyo / RIKEN AIP)
  Taira Tsuchiya (The University of Tokyo / RIKEN AIP)
  Junya Honda (Kyoto University / RIKEN AIP)
• Follow-the-Perturbed-Leader with Fr\'{e}chet-type Tail Distributions: Optimality in Adversarial Bandits and Best-of-Both-Worlds
  Jongyeong Lee (Seoul National University)
  Junya Honda (Kyoto University / RIKEN AIP)
  Shinji Ito (The University of Tokyo / RIKEN AIP)
  Min-hwan Oh (Seoul National University)
• Learning sum of ridge functions: Efficient gradient-based training and computational hardness
  Kazusato Oko (The University of Tokyo / RIKEN AIP)
  Yujin Song (The University of Tokyo)
  Taiji Suzuki (The University of Tokyo / RIKEN AIP)
  Denny Wu (New York University / Flatiron Institute)
  *alphabetical order

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