Center for Advanced Intelligence Project

14 papers have been accepted at AISTATS 2025. a major conference on machine learning.

[Acceptance rate]
There are 583 accepted papers from 1,861 submissions, leading to a 31.3 percent acceptance rate.

AISTATS 2025

[Accepted Papers]

• Oral

• Near-Optimal Algorithm for Non-Stationary Kernelized Bandits
  Shogo Iwazaki (MI-6 Ltd.)
  Shion Takeno (Nagoya University / RIKEN AIP)

• Poster

• Clustered Invariant Risk Minimization
  Tomoya Murata (NTT DATA Mathematical Systems Inc. / RIKEN AIP)
  Atsushi Nitanda (A*STAR)
  Taiji Suzuki (The University of Tokyo / RIKEN AIP)
• Domain Adaptation and Entanglement: an Optimal Transport Perspective
  Okan Koc (RIKEN AIP)
  Alexander Soen (Australian National University / RIKEN AIP)
  Chao-Kai Chiang (The University of Tokyo)
  Masashi Sugiyama (RIKEN AIP/ The University of Tokyo)
• Energy-consistent Neural Operators for Hamiltonian and Dissipative Partial Differential Equations
  Yusuke Tanaka (NTT CS labs)
  Tomoharu Iwata (NTT CS labs)
  Naonori Ueda (RIKEN AIP)
  Takaharu Yaguchi (Kobe University)
• Inverse Optimization with Prediction Market: A Characterization of Scoring Rules for Elciting System States
  Han Bao (Kyoto University)
  Shinsaku Sakaue (The University of Tokyo / RIKEN AIP)
• LC-Tsallis-INF: Generalized Best-of-Both-Worlds Linear Contextual Bandits
  Masahiro Kato (Mizuho-DL Financial Technology Co., Ltd / The University of Tokyo)
  Shinji Ito (The University of Tokyo / RIKEN AIP)
• Learning a Single Index Model from Anisotropic Data with Vanilla Stochastic
  Gradient Descent
  Guillaume Braun (RIKEN ), Minh Ha Quang (RIKEN)
  Masaaki Imaizumi(RIKEN AIP / The University of Tokyo)
• Learning Stochastic Nonlinear Dynamics with Embedded Latent Transfer Operators
  Naichang Ke (Osaka University)
  Ryogo Tanaka (Osaka University)
  Yoshinobu Kawahara (Osaka University / RIKEN AIP)
• Multi-Player Approaches for Dueling Bandits
  Or Raveh (The University of Tokyo / RIKEN AIP)
  Junya Honda (Kyoto University / RIKEN AIP)
  Masashi Sugiyama (RIKEN AIP / The University of Tokyo)
• No-Regret Bayesian Optimization with Stochastic Observation Failures
  Shogo Iwazaki (MI-6 Ltd.)
  Tomohiko Tanabe (MI-6 Ltd.)
  Mitsuru Irie (MI-6 Ltd.)
  Shion Takeno (Nagoya University / RIKEN AIP)
  Kota Matsui (Nagoya University)
  Yu Inatsu (Nagoya Institute of Technology)
• Revisiting Online Learning Approach to Inverse Linear Optimization: A Fenchel–Young Loss Perspective and Gap-Dependent Regret Analysis
  Shinsaku Sakaue (The University of Tokyo / RIKEN AIP)
  Han Bao (Kyoto University)
  Taira Tsuchiya (The University of Tokyo / RIKEN AIP)
• Quantifying the Optimization and Generalization Advantages of Graph Neural Networks Over Multilayer Perceptrons
  Wei Huang (RIKEN AIP)
  Yuan Cao (The University of Hong Kong)
  Haonan Wang (National University of Singapore)
  Xin Cao (The University of New South Wales)
  Taiji Suzuki (The University of Tokyo / RIKEN AIP)
• Statistical Test for Auto Feature Engineering by Selective Inference
  Tatsuya Matsukawa (Nagoya University)
  Tomohiro Shiraishi (Nagoya University)
  Shuichi Nishino (Nagoya University / RIKEN AIP)
  Teruyuki Katsuoka (Nagoya University)
  Ichiro Takeuchi (Nagoya University / RIKEN AIP)
• Stochastic Gradient Descent for Bézier Simplex Representation of Pareto Set in Multi-Objective Optimization
  Yasunari Hikima (Fujitsu Research and Development Center Co. Ltm.)
  Ken Kobayashi (Institute of Science Tokyo)
  Akinori Tanaka (RIKEN AIP)
  Akiyoshi Sannai (Kyoto University)
  Naoki Hamada (KLab Inc.)

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