Center for Advanced Intelligence Project

35 papers were accepted at NeurIPS 2023, which is known as a top conference on machine learning.
For more details, please refer to the link below:
[NeurIPS 2023 ]
There were 12,343 full paper submissions to NeurIPS this year, of which the program committee accepted 26.１% for presentation at the conference.

Spotlight

• Efficient Adversarial Contrastive Learning via Robustness-Aware Coreset Selection
  Xilie Xu (National University of Singapore)
  Jingfeng Zhang (RIKEN AIP/ University of Auckland)
  Feng Liu (University of Melbourne / RIKEN AIP)
  Masashi Sugiyama (RIKEN AIP / The University of Tokyo)
  Mohan Kankanhalli (National University of Singapore)
• Generalizing Importance Weighting to A Universal Solver for Distribution Shift Problems
  Tongtong Fang (The University of Tokyo)
  Nan Lu (Eberhard-Karls-Universitaet Tuebingen / RIKEN AIP)
  Gang Niu (RIKEN AIP)
  Masashi Sugiyama (RIKEN AIP / The University of Tokyo)
• Mean-field Langevin dynamics: Time-space discretization, stochastic gradient, and variance reduction
  Taiji Suzuki (The University of Tokyo / RIKEN AIP)
  Denny Wu (New York University / Flatiron Institute)+
  Atsushi Nitanda (Kyushu Institute of Technology / RIKEN AIP)
• Online (Multinomial) Logistic Bandit: Improved Regret and Constant Computation Cost
  Yu-Jie Zhang (The University of Tokyo)
  Masashi Sugiyama (RIKEN AIP/ The University of Tokyo)

Poster

• Adapting to Continuous Covariate Shift via Online Density Ratio Estimation
  Yu-Jie Zhang (The University of Tokyo)
  Zhen-Yu Zhang (RIKEN AIP)
  Peng Zhao (Nanjing University / RIKEN AIP)
  Masashi Sugiyama (RIKEN AIP/ The University of Tokyo)
• Analyzing Generalization of Neural Networks through Loss Path Kernels
  Yilan Chen (University of California, San Diego)
  Wei Huang (RIKEN AIP)
  Hao Wang (MIT-IBM Watson AI Lab)
  Charlotte Loh (Massachusetts Institute of Technology)
  Akash Srivastava (Massachusetts Institute of Technology)
  Lam M. Nguyen (IBM Research)
  Tsui-Wei Weng (University of California, San Diego)
• Bandit Task Assignment with Unknown Processing Time
  Shinji Ito (NEC)
  Daisuke Hatano (RIKEN AIP)
  Hanna Sumita (Tokyo Institute of Technology)
  Kei Takemura (NEC)
  Takuro Fukunaga (Chuo University)
  Naonori Kakimura (Keio University)
  Ken-Ichi Kawarabayashi (National Institute of Informatics)
• Binary Classification with Confidence Difference
  Wei Wang (The University of Tokyo / RIKEN AIP)
  Lei Feng (Nanyang Technological University / RIKEN AIP)
  Yuchen Jiang (Alibaba Group)
  Gang Niu (RIKEN AIP)
  Min-Ling Zhang (Southeast University)
  Masashi Sugiyama (RIKEN AIP / The University of Tokyo)
• Calibrating Neural Simulation-Based Inference with Differentiable Coverage Probability
  Maciej Falkiewicz (HES-SO)
  Naoya Takeishi (UTokyo / RIKEN AIP)
  Imahn Shekhzadeh (HES-SO)
  Antoine Wehenkel (Apple)
  Arnaud Delaunoy (ULiège)
  Gilles Louppe (ULiège)
  Alexandros Kalousis (HES-SO)
• CityRefer: Geography-aware 3D Visual Grounding Dataset on City-scale Point Cloud Data
  Taiki Miyanishi (ATR/ RIKEN AIP)
  Fumiya Kitamori (Tokyo Institute of Technology)
  Shuhei Kurita (RIKEN AIP)
  Jungdae Lee (Tokyo Institute of Technology)
  Motoaki Kawanabe (ATR)
  Nakamasa Inoue (Tokyo Institute of Technology)
• Class-Distribution-Aware Pseudo-Labeling for Semi-Supervised Multi-Label Learning
  Ming-Kun Xie (Nanjing University of Aeronautics and Astronautics)+
  Jia-Hao Xiao (Nanjing University of Aeronautics and Astronautics)
  Hao-Zhe Liu (Nanjing University of Aeronautics and Astronautics)
  Gang Niu (RIKEN AIP)
  Masashi Sugiyama (RIKEN AIP / The University of Tokyo)
  Sheng-Jun Huang (Nanjing University of Aeronautics and Astronautics)
• Deep learning with kernels through RKHM and the Perron-Frobenius operator
  Yuka Hashimoto (NTT / RIKEN AIP)
  Masahiro Ikeda (RIKEN AIP)
  Hachem Kadri (Aix-Marseille University)
• Demographic Parity Constrained Minimax Optimal Regression under Linear Model
  Kazuto Fukuchi (University of Tsukuba / RIKEN AIP)
  Jun Sakuma (Tokyo Institute of Technology / RIKEN AIP).
• Detection Based Part-level Articulated Object Reconstruction from Single RGBD Image
  Yuki Kawana (The University of Tokyo)
  Tatsuya Harada (The University of Tokyo / RIKEN AIP)
• Diversified Outlier Exposure for Out-of-Distribution Detection via Informative Extrapolation
  Jianing Zhu (Hong Kong Baptist University)+
  Geng Yu (Shanghai Jiaotong University)
  Jiangchao Yao (Shanghai Jiaotong University)
  Tongliang Liu (University of Sydney / RIKEN AIP)
  Gang Niu (RIKEN AIP)
  Masashi Sugiyama (RIKEN AIP/ The University of Tokyo)
  Bo Han (Hong Kong Baptist University / RIKEN AIP)
• Enhancing Adversarial Contrastive Learning via Adversarial Invariant Regularization
  Xilie Xu (National University of Singapore)
  Jingfeng Zhang (RIKEN AIP / University of Auckland)
  Feng Liu (University of Melbourne / RIKEN AIP)
  Masashi Sugiyama (RIKEN AIP / The University of Tokyo)
  Mohan Kankanhalli (National University of Singapore)
• Failure-Aware Gaussian Process Optimization with Regret Bounds
  Shogo Iwazaki (MI-6 Ltd.)
  Shion Takeno (RIKEN AIP)
  Tomohiko Tanabe (MI-6 Ltd.)
  Mitsuru Irie (MI-6 Ltd.)
• Feature learning via mean-field Langevin dynamics: classifying sparse parities and beyond
  Taiji Suzuki (The University of Tokyo / RIKEN AIP)
  Denny Wu (New York University / Flatiron Institute)+
  Kazusato Oko (The University of Tokyo / RIKEN AIP)
  Atsushi Nitanda (Kyushu Institute of Technology / RIKEN AIP)
• Fed-CO2: Cooperation of Online and Offline Models for Severe Data Heterogeneity in Federated Learning
  Zhongyi Cai (ShanghaiTech University)
  Ye Shi (ShanghaiTech University)
  Wei Huang (RIKEN AIP)
  Jingya Wang (ShanghaiTech University)
• GeoPhy: Differentiable Phylogenetic Inference via Geometric Gradients of Tree Topologies
  Takahiro Mimori (Waseda University / RIKEN AIP)
  Michiaki Hamada (Waseda University / AIST-Waseda CBBD-OIL / Nippon Medical School)
• Gradient-Based Feature Learning under Structured Data
  Alireza Mousavi-Hosseini (University of Toronto)
  Denny Wu (New York University / Flatiron Institute)+
  Taiji Suzuki (The University of Tokyo / RIKEN AIP)
  Murat A Erdogdu (University of Toronto / Vector Institute)
• High-dimensional Contextual Bandit Problem without Sparsity
  Junpei Komiyama (New York University)
  Masaaki Imaizumi (The University of Tokyo / RIKEN AIP)
• Imitation Learning from Vague Feedback
  Xin-Qiang Cai (The University of Tokyo)
  Yu-Jie Zhang (The University of Tokyo)
  Chao-Kai Chiang (The University of Tokyo)
  Masashi Sugiyama (RIKEN AIP / The University of Tokyo)
• Learning in the Presence of Low-dimensional Structure: A Spiked Random Matrix Perspective
  Jimmy Ba (University of Toronto / Vector Institute / xAI)
  Murat A Erdogdu (University of Toronto / Vector Institute)
  Taiji Suzuki (The University of Tokyo / RIKEN AIP)
  Zhichao Wang (University of California, San Diego)
  Denny Wu (New York University / Flatiron Institute)+
• Learning Pareto-Optimal Policies for Multi-Objective Joint Distribution
  Xin-Qiang Cai (The University of Tokyo)
  Pushi Zhang (Microsoft)
  Li Zhao (Tsinghua University)
  Jiang Bian (Microsoft)
  Masashi Sugiyama (RIKEN AIP / The University of Tokyo)
  Ashley Juan Llorens (Microsoft)
• Many-body Approximation for Non-negative Tensors
  Kazu Ghalamkari (RIKEN AIP)
  Mahito Sugiyama (NII)
  Yoshinobu Kawahara (Osaka University / RIKEN AIP)
• On the Overlooked Pitfalls of Weight Decay and How to Mitigate Them: A Gradient-Norm Perspective
  Zeke Xie (Baidu)
  Xhiqiang Xu (Mohamed bin Zayed University of Artificial Intelligence)
  Jingzhao Zhang (Tsinghua University)
  Issei Sato (The University of Tokyo)
  Masashi Sugiyama (RIKEN AIP / The University of Tokyo)
• RealTime QA: What’s the Answer Right Now?
  Jungo Kasai (University of Washington)
  Keisuke Sakaguchi (Tohoku University, RIKEN AIP)
  Yoichi Takahashi (Tohoku University)
  Ronan Le Bras (Allen Institute for AI)
  Akari Asai (University of Washington)
  Xinyan Velocity Yu (University of Washington)
  Dragomir Radev (Yale University)
  Noah A. Smith (University of Washington, Allen Institute for AI)
  Yejin Choi (University of Washington, Allen Institute for AI)
  Kentaro Inui (Tohoku University, RIKEN AIP)
• Self-Weighted Contrastive Learning among Multiple Views for Mitigating Representation Degeneration
  Jie Xu (University of Electronic Science and Technology of China)
  Shuo Chen (RIKEN AIP)
  Yazhou Ren (University of Electronic Science and Technology of China)
  Xiaoshuang Shi (University of Electronic Science and Technology of China)
  Heng Tao Shen (University of Electronic Science and Technology of China)
  Gang Niu (RIKEN AIP)
  Xiaofeng Zhu (University of Electronic Science and Technology of China)
• Stability-penalty-adaptive follow-the-regularized-leader: Sparsity, game-dependency, and best-of-both-worlds
  Taira Tsuchiya (Kyoto University / RIKEN AIP)
  Shinji Ito (NEC)
  Junya Honda (Kyoto University / RIKEN AIP)
• The Memory Perturbation Equation: Understanding Model’s Sensitivity to Data
  Peter Nickl (RIKEN AIP)
  Lu Xu (RIKEN AIP)
  Dharmesh Tailor (University of Amsterdam, work done at RIKEN AIP as a tech-staff)
  Thomas Moellenhoff (RIKEN AIP)
  Mohammad Emtiyaz Khan (RIKEN AIP)
• Time-Independent Information-Theoretic Generalization Bounds for SGLD.
  Futoshi Futami* (Osaka University / RIKEN AIP)
  Masahiro Fujisawa* (RIKEN AIP)
  *: Equal contribution
• Transformed Low-Rank Parameterization Can Help Robust Generalization for Tensor Neural Networks
  Andong Wang (RIKEN AIP)
  Chao Li (RIKEN AIP)
  Mingyuan Bai (RIKEN AIP)
  Zhong Jin (Nanjing University of Science and Technology)
  Guoxu Zhou (Guangdong University of Technology)
  Qibin Zhao (RIKEN AIP)
• Understanding and Improving Feature Learning for Out-of-Distribution Generalization
  Wei Huang (RIKEN AIP) [Equal Contribution]
  Yongqiang Chen (The Chinese University of Hong Kong) [Equal Contribution]
  Kaiwen Zhou (The Chinese University of Hong Kong) [Equal Contribution]
  Yatao Bian (Tencent AI Lab)
  Bo Han (Hong Kong Baptist University / RIKEN AIP)
  James Cheng (The Chinese University of Hong Kong)
• Undirected Probabilistic Model for Tensor Decomposition
  Zerui Tao (Tokyo University of Agriculture and Technology / RIKEN AIP)
  Toshihisa Tanaka (Tokyo University of Agriculture and Technology / RIKEN AIP)
  Qibin Zhao (RIKEN AIP / Tokyo University of Agriculture and Technology)

+Past interns of RIKEN AIP

Related Laboratories