Masashi Sugiyama

ORCID

Publication Activity (10 Years)

Years Active: 1999-2024
Publications (10 Years): 429

Top Venues

Publications

Soichiro Nishimori, Xin-Qiang Cai, Johannes Ackermann, Masashi Sugiyama
Leveraging Domain-Unlabeled Data in Offline Reinforcement Learning across Two Domains. CoRR (2024)
Hao Chen, Yujin Han, Diganta Misra, Xiang Li, Kai Hu, Difan Zou, Masashi Sugiyama, Jindong Wang, Bhiksha Raj
Slight Corruption in Pre-training Data Makes Better Diffusion Models. CoRR (2024)
Johannes Ackermann, Takayuki Osa, Masashi Sugiyama
Offline Reinforcement Learning from Datasets with Structured Non-Stationarity. CoRR (2024)
Shintaro Nakamura, Masashi Sugiyama
Fixed-Budget Real-Valued Combinatorial Pure Exploration of Multi-Armed Bandit. AISTATS (2024)
Hao Chen, Jindong Wang, Zihan Wang, Ran Tao, Hongxin Wei, Xing Xie, Masashi Sugiyama, Bhiksha Raj
Learning with Noisy Foundation Models. CoRR (2024)
Zhen-Yu Zhang, Siwei Han, Huaxiu Yao, Gang Niu, Masashi Sugiyama
Generating Chain-of-Thoughts with a Direct Pairwise-Comparison Approach to Searching for the Most Promising Intermediate Thought. CoRR (2024)
Guillaume Braun, Masashi Sugiyama
VEC-SBM: Optimal Community Detection with Vectorial Edges Covariates. CoRR (2024)
Ming-Kun Xie, Jiahao Xiao, Pei Peng, Gang Niu, Masashi Sugiyama, Sheng-Jun Huang
Counterfactual Reasoning for Multi-Label Image Classification via Patching-Based Training. CoRR (2024)
Hao Chen, Jindong Wang, Lei Feng, Xiang Li, Yidong Wang, Xing Xie, Masashi Sugiyama, Rita Singh, Bhiksha Raj
A General Framework for Learning from Weak Supervision. CoRR (2024)
Or Raveh, Junya Honda, Masashi Sugiyama
Multi-Player Approaches for Dueling Bandits. CoRR (2024)
Kunda Yan, Sen Cui, Abudukelimu Wuerkaixi, Jingfeng Zhang, Bo Han, Gang Niu, Masashi Sugiyama, Changshui Zhang
Balancing Similarity and Complementarity for Federated Learning. CoRR (2024)
Qizhou Wang, Bo Han, Puning Yang, Jianing Zhu, Tongliang Liu, Masashi Sugiyama
Unlearning with Control: Assessing Real-world Utility for Large Language Model Unlearning. CoRR (2024)
Guillaume Braun, Masashi Sugiyama
VEC-SBM: Optimal Community Detection with Vectorial Edges Covariates. AISTATS (2024)
Shintaro Nakamura, Masashi Sugiyama
Thompson Sampling for Real-Valued Combinatorial Pure Exploration of Multi-Armed Bandit. AAAI (2024)
Jianing Zhu, Bo Han, Jiangchao Yao, Jianliang Xu, Gang Niu, Masashi Sugiyama
Decoupling the Class Label and the Target Concept in Machine Unlearning. CoRR (2024)
Jialiang Tang, Shuo Chen, Gang Niu, Hongyuan Zhu, Joey Tianyi Zhou, Chen Gong, Masashi Sugiyama
Direct Distillation between Different Domains. CoRR (2024)
Ziqing Fan, Shengchao Hu, Jiangchao Yao, Gang Niu, Ya Zhang, Masashi Sugiyama, Yanfeng Wang
Locally Estimated Global Perturbations are Better than Local Perturbations for Federated Sharpness-aware Minimization. CoRR (2024)
Qingxiuxiong Dong, Toshimitsu Kaneko, Masashi Sugiyama
An offline learning of behavior correction policy for vision-based robotic manipulation. ICRA (2024)
Jongyeong Lee, Chao-Kai Chiang, Masashi Sugiyama
The Choice of Noninformative Priors for Thompson Sampling in Multiparameter Bandit Models. AAAI (2024)
Masashi Sugiyama
Overcoming Continuous Distribution Shifts: Challenges in Online Machine Learning. BCI (2024)
Hao Chen, Jindong Wang, Ankit Shah, Ran Tao, Hongxin Wei, Xing Xie, Masashi Sugiyama, Bhiksha Raj
Understanding and Mitigating the Label Noise in Pre-training on Downstream Tasks. ICLR (2024)
Yuting Tang, Xin-Qiang Cai, Yao-Xiang Ding, Qiyu Wu, Guoqing Liu, Masashi Sugiyama
Reinforcement Learning from Bagged Reward: A Transformer-based Approach for Instance-Level Reward Redistribution. CoRR (2024)
Jiahao Xiao, Ming-Kun Xie, Heng-Bo Fan, Gang Niu, Masashi Sugiyama, Sheng-Jun Huang
Dual-Decoupling Learning and Metric-Adaptive Thresholding for Semi-Supervised Multi-Label Learning. CoRR (2024)
Ayoub Ghriss, Masashi Sugiyama, Alessandro Lazaric
Reinforcement Learning with Options and State Representation. CoRR (2024)
Shuo Chen, Gang Niu, Chen Gong, Okan Koc, Jian Yang, Masashi Sugiyama
Robust Similarity Learning with Difference Alignment Regularization. ICLR (2024)
Jiaqi Lv, Biao Liu, Lei Feng, Ning Xu, Miao Xu, Bo An, Gang Niu, Xin Geng, Masashi Sugiyama
On the Robustness of Average Losses for Partial-Label Learning. IEEE Trans. Pattern Anal. Mach. Intell. 46 (5) (2024)
Yuki Tanaka, Shuhei M. Yoshida, Takashi Shibata, Makoto Terao, Takayuki Okatani, Masashi Sugiyama
Appearance-Based Curriculum for Semi-Supervised Learning with Multi-Angle Unlabeled Data. WACV (2024)
Jingfeng Zhang, Bo Song, Haohan Wang, Bo Han, Tongliang Liu, Lei Liu, Masashi Sugiyama
BadLabel: A Robust Perspective on Evaluating and Enhancing Label-Noise Learning. IEEE Trans. Pattern Anal. Mach. Intell. 46 (6) (2024)
Abudukelimu Wuerkaixi, Sen Cui, Jingfeng Zhang, Kunda Yan, Bo Han, Gang Niu, Lei Fang, Changshui Zhang, Masashi Sugiyama
Accurate Forgetting for Heterogeneous Federated Continual Learning. ICLR (2024)
Jiaheng Wei, Zhaowei Zhu, Gang Niu, Tongliang Liu, Sijia Liu, Masashi Sugiyama, Yang Liu
Fairness Improves Learning from Noisily Labeled Long-Tailed Data. CoRR (2023)
Jingfeng Zhang, Bo Song, Bo Han, Lei Liu, Gang Niu, Masashi Sugiyama
Assessing Vulnerabilities of Adversarial Learning Algorithm through Poisoning Attacks. CoRR (2023)
Tingting Zhao, Ying Wang, Wei Sun, Yarui Chen, Gang Niu, Masashi Sugiyama
Representation learning for continuous action spaces is beneficial for efficient policy learning. Neural Networks 159 (2023)
Ruijiang Dong, Feng Liu, Haoang Chi, Tongliang Liu, Mingming Gong, Gang Niu, Masashi Sugiyama, Bo Han
Diversity-enhancing Generative Network for Few-shot Hypothesis Adaptation. CoRR (2023)
Salah Ghamizi, Jingfeng Zhang, Maxime Cordy, Mike Papadakis, Masashi Sugiyama, Yves Le Traon
GAT: Guided Adversarial Training with Pareto-optimal Auxiliary Tasks. CoRR (2023)
Shota Nakajima, Masashi Sugiyama
Positive-unlabeled classification under class-prior shift: a prior-invariant approach based on density ratio estimation. Mach. Learn. 112 (3) (2023)
Penghui Yang, Ming-Kun Xie, Chen-Chen Zong, Lei Feng, Gang Niu, Masashi Sugiyama, Sheng-Jun Huang
Multi-Label Knowledge Distillation. CoRR (2023)
Tongtong Fang, Nan Lu, Gang Niu, Masashi Sugiyama
Generalizing Importance Weighting to A Universal Solver for Distribution Shift Problems. CoRR (2023)
Xilie Xu, Jingfeng Zhang, Feng Liu, Masashi Sugiyama, Mohan S. Kankanhalli
Efficient Adversarial Contrastive Learning via Robustness-Aware Coreset Selection. CoRR (2023)
Xilie Xu, Jingfeng Zhang, Feng Liu, Masashi Sugiyama, Mohan S. Kankanhalli
Efficient Adversarial Contrastive Learning via Robustness-Aware Coreset Selection. NeurIPS (2023)
Yosuke Otsubo, Naoya Otani, Megumi Chikasue, Mineyuki Nishino, Masashi Sugiyama
Root cause estimation of faults in production processes: a novel approach inspired by approximate Bayesian computation. Int. J. Prod. Res. 61 (5) (2023)
Zeke Xie, Zhiqiang Xu, Jingzhao Zhang, Issei Sato, Masashi Sugiyama
On the Overlooked Pitfalls of Weight Decay and How to Mitigate Them: A Gradient-Norm Perspective. NeurIPS (2023)
Wei-I Lin, Gang Niu, Hsuan-Tien Lin, Masashi Sugiyama
Enhancing Label Sharing Efficiency in Complementary-Label Learning with Label Augmentation. CoRR (2023)
Xilie Xu, Jingfeng Zhang, Feng Liu, Masashi Sugiyama, Mohan S. Kankanhalli
Enhancing Adversarial Contrastive Learning via Adversarial Invariant Regularization. CoRR (2023)
Yu-Jie Zhang, Zhen-Yu Zhang, Peng Zhao, Masashi Sugiyama
Adapting to Continuous Covariate Shift via Online Density Ratio Estimation. NeurIPS (2023)
Yivan Zhang, Masashi Sugiyama
Enriching Disentanglement: Definitions to Metrics. CoRR (2023)
Jianing Zhu, Yu Geng, Jiangchao Yao, Tongliang Liu, Gang Niu, Masashi Sugiyama, Bo Han
Diversified Outlier Exposure for Out-of-Distribution Detection via Informative Extrapolation. NeurIPS (2023)
Jingfeng Zhang, Bo Song, Haohan Wang, Bo Han, Tongliang Liu, Lei Liu, Masashi Sugiyama
BadLabel: A Robust Perspective on Evaluating and Enhancing Label-noise Learning. CoRR (2023)
Ruijiang Dong, Feng Liu, Haoang Chi, Tongliang Liu, Mingming Gong, Gang Niu, Masashi Sugiyama, Bo Han
Diversity-enhancing Generative Network for Few-shot Hypothesis Adaptation. ICML (2023)
Wei Wang, Lei Feng, Yuchen Jiang, Gang Niu, Min-Ling Zhang, Masashi Sugiyama
Binary Classification with Confidence Difference. NeurIPS (2023)
Jialiang Tang, Shuo Chen, Gang Niu, Masashi Sugiyama, Chen Gong
Distribution Shift Matters for Knowledge Distillation with Webly Collected Images. ICCV (2023)
Jialiang Tang, Shuo Chen, Gang Niu, Masashi Sugiyama, Chen Gong
Distribution Shift Matters for Knowledge Distillation with Webly Collected Images. CoRR (2023)
Jongyeong Lee, Junya Honda, Chao-Kai Chiang, Masashi Sugiyama
Optimality of Thompson Sampling with Noninformative Priors for Pareto Bandits. ICML (2023)
Yivan Zhang, Masashi Sugiyama
A Category-theoretical Meta-analysis of Definitions of Disentanglement. ICML (2023)
Jongyeong Lee, Junya Honda, Masashi Sugiyama
Thompson Exploration with Best Challenger Rule in Best Arm Identification. CoRR (2023)
Ming-Kun Xie, Jiahao Xiao, Gang Niu, Masashi Sugiyama, Sheng-Jun Huang
Class-Distribution-Aware Pseudo Labeling for Semi-Supervised Multi-Label Learning. CoRR (2023)
Nobutaka Ito, Masashi Sugiyama
Audio Signal Enhancement with Learning from Positive and Unlabeled Data. ICASSP (2023)
Salah Ghamizi, Jingfeng Zhang, Maxime Cordy, Mike Papadakis, Masashi Sugiyama, Yves Le Traon
GAT: Guided Adversarial Training with Pareto-optimal Auxiliary Tasks. ICML (2023)
Yivan Zhang, Masashi Sugiyama
A Category-theoretical Meta-analysis of Definitions of Disentanglement. CoRR (2023)
Xin-Qiang Cai, Yao-Xiang Ding, Zi-Xuan Chen, Yuan Jiang, Masashi Sugiyama, Zhi-Hua Zhou
Seeing Differently, Acting Similarly: Heterogeneously Observable Imitation Learning. ICLR (2023)
Shintaro Nakamura, Masashi Sugiyama
Fixed-Budget Real-Valued Combinatorial Pure Exploration of Multi-Armed Bandit. CoRR (2023)
Jongyeong Lee, Junya Honda, Chao-Kai Chiang, Masashi Sugiyama
Optimality of Thompson Sampling with Noninformative Priors for Pareto Bandits. CoRR (2023)
Yuhao Wu, Xiaobo Xia, Jun Yu, Bo Han, Gang Niu, Masashi Sugiyama, Tongliang Liu
Making Binary Classification from Multiple Unlabeled Datasets Almost Free of Supervision. CoRR (2023)
Sora Satake, Yoshihiro Nagano, Masashi Sugiyama, Masahiro Fujiwara, Yasutoshi Makino, Hiroyuki Shinoda
Analysis of Pleasantness Evoked by Various Airborne Ultrasound Tactile Stimuli Using Pairwise Comparisons and the Bradley-Terry Model. CoRR (2023)
Takashi Ishida, Ikko Yamane, Nontawat Charoenphakdee, Gang Niu, Masashi Sugiyama
Is the Performance of My Deep Network Too Good to Be True? A Direct Approach to Estimating the Bayes Error in Binary Classification. ICLR (2023)
Shintaro Nakamura, Masashi Sugiyama
Combinatorial Pure Exploration of Multi-Armed Bandit with a Real Number Action Class. CoRR (2023)
Shintaro Nakamura, Masashi Sugiyama
Thompson Sampling for Real-Valued Combinatorial Pure Exploration of Multi-Armed Bandit. CoRR (2023)
Ming-Kun Xie, Jiahao Xiao, Hao-Zhe Liu, Gang Niu, Masashi Sugiyama, Sheng-Jun Huang
Class-Distribution-Aware Pseudo-Labeling for Semi-Supervised Multi-Label Learning. NeurIPS (2023)
Wei Wang, Lei Feng, Yuchen Jiang, Gang Niu, Min-Ling Zhang, Masashi Sugiyama
Binary Classification with Confidence Difference. CoRR (2023)
Xin-Qiang Cai, Pushi Zhang, Li Zhao, Jiang Bian, Masashi Sugiyama, Ashley Llorens
Distributional Pareto-Optimal Multi-Objective Reinforcement Learning. NeurIPS (2023)
Chao-Kai Chiang, Masashi Sugiyama
Unified Risk Analysis for Weakly Supervised Learning. CoRR (2023)
Shuo Chen, Chen Gong, Xiang Li, Jian Yang, Gang Niu, Masashi Sugiyama
Boundary-restricted metric learning. Mach. Learn. 112 (12) (2023)
Xin-Qiang Cai, Yu-Jie Zhang, Chao-Kai Chiang, Masashi Sugiyama
Imitation Learning from Vague Feedback. NeurIPS (2023)
Chen Gong, Yongliang Ding, Bo Han, Gang Niu, Jian Yang, Jane You, Dacheng Tao, Masashi Sugiyama
Class-Wise Denoising for Robust Learning Under Label Noise. IEEE Trans. Pattern Anal. Mach. Intell. 45 (3) (2023)
Tingting Zhao, S. Wu, G. Li, Y. Chen, Gang Niu, Masashi Sugiyama
Learning Intention-Aware Policies in Deep Reinforcement Learning. Neural Comput. 35 (10) (2023)
Wentao Yu, Shuo Chen, Chen Gong, Gang Niu, Masashi Sugiyama
Atom-Motif Contrastive Transformer for Molecular Property Prediction. CoRR (2023)
Xilie Xu, Jingfeng Zhang, Feng Liu, Masashi Sugiyama, Mohan S. Kankanhalli
Enhancing Adversarial Contrastive Learning via Adversarial Invariant Regularization. NeurIPS (2023)
Jongyeong Lee, Junya Honda, Masashi Sugiyama
Thompson Exploration with Best Challenger Rule in Best Arm Identification. ACML (2023)
Hao Chen, Jindong Wang, Ankit Shah, Ran Tao, Hongxin Wei, Xing Xie, Masashi Sugiyama, Bhiksha Raj
Understanding and Mitigating the Label Noise in Pre-training on Downstream Tasks. CoRR (2023)
Jianing Zhu, Geng Yu, Jiangchao Yao, Tongliang Liu, Gang Niu, Masashi Sugiyama, Bo Han
Diversified Outlier Exposure for Out-of-Distribution Detection via Informative Extrapolation. CoRR (2023)
Yu-Jie Zhang, Masashi Sugiyama
Online (Multinomial) Logistic Bandit: Improved Regret and Constant Computation Cost. NeurIPS (2023)
Yu-Jie Zhang, Zhen-Yu Zhang, Peng Zhao, Masashi Sugiyama
Adapting to Continuous Covariate Shift via Online Density Ratio Estimation. CoRR (2023)
Zhenguo Wu, Jiaqi Lv, Masashi Sugiyama
Learning With Proper Partial Labels. Neural Comput. 35 (1) (2023)
Hao Chen, Ankit Shah, Jindong Wang, Ran Tao, Yidong Wang, Xing Xie, Masashi Sugiyama, Rita Singh, Bhiksha Raj
Imprecise Label Learning: A Unified Framework for Learning with Various Imprecise Label Configurations. CoRR (2023)
Penghui Yang, Ming-Kun Xie, Chen-Chen Zong, Lei Feng, Gang Niu, Masashi Sugiyama, Sheng-Jun Huang
Multi-Label Knowledge Distillation. ICCV (2023)
Jongyeong Lee, Chao-Kai Chiang, Masashi Sugiyama
Asymptotically Optimal Thompson Sampling Based Policy for the Uniform Bandits and the Gaussian Bandits. CoRR (2023)
Wei Wang, Takashi Ishida, Yu-Jie Zhang, Gang Niu, Masashi Sugiyama
Learning with Complementary Labels Revisited: A Consistent Approach via Negative-Unlabeled Learning. CoRR (2023)
Tongtong Fang, Nan Lu, Gang Niu, Masashi Sugiyama
Generalizing Importance Weighting to A Universal Solver for Distribution Shift Problems. NeurIPS (2023)
Xilie Xu, Jingfeng Zhang, Feng Liu, Masashi Sugiyama, Mohan S. Kankanhalli
Adversarial Attack and Defense for Non-Parametric Two-Sample Tests. ICML (2022)
Nobutaka Ito, Masashi Sugiyama
Audio Signal Enhancement with Learning from Positive and Unlabelled Data. CoRR (2022)
Kenji Doya, Karl J. Friston, Masashi Sugiyama, Joshua B. Tenenbaum
Neural Networks special issue on Artificial Intelligence and Brain Science. Neural Networks 155 (2022)
Shintaro Nakamura, Han Bao, Masashi Sugiyama
Robust computation of optimal transport by β-potential regularization. CoRR (2022)
Haoang Chi, Feng Liu, Wenjing Yang, Long Lan, Tongliang Liu, Bo Han, Gang Niu, Mingyuan Zhou, Masashi Sugiyama
Meta Discovery: Learning to Discover Novel Classes given Very Limited Data. ICLR (2022)
Yuzhou Cao, Tianchi Cai, Lei Feng, Lihong Gu, Jinjie Gu, Bo An, Gang Niu, Masashi Sugiyama
Generalizing Consistent Multi-Class Classification with Rejection to be Compatible with Arbitrary Losses. NeurIPS (2022)
De Cheng, Tongliang Liu, Yixiong Ning, Nannan Wang, Bo Han, Gang Niu, Xinbo Gao, Masashi Sugiyama
Instance-Dependent Label-Noise Learning with Manifold-Regularized Transition Matrix Estimation. CVPR (2022)
Yuting Tang, Nan Lu, Tianyi Zhang, Masashi Sugiyama
Multi-class Classification from Multiple Unlabeled Datasets with Partial Risk Regularization. ACML (2022)
Yuangang Pan, Ivor W. Tsang, Weijie Chen, Gang Niu, Masashi Sugiyama
Fast and Robust Rank Aggregation against Model Misspecification. J. Mach. Learn. Res. 23 (2022)
Yu Yao, Tongliang Liu, Bo Han, Mingming Gong, Gang Niu, Masashi Sugiyama, Dacheng Tao
Rethinking Class-Prior Estimation for Positive-Unlabeled Learning. ICLR (2022)
Ziqing Lu, Chang Xu, Bo Du, Takashi Ishida, Lefei Zhang, Masashi Sugiyama
LocalDrop: A Hybrid Regularization for Deep Neural Networks. IEEE Trans. Pattern Anal. Mach. Intell. 44 (7) (2022)
Takashi Ishida, Ikko Yamane, Nontawat Charoenphakdee, Gang Niu, Masashi Sugiyama
Is the Performance of My Deep Network Too Good to Be True? A Direct Approach to Estimating the Bayes Error in Binary Classification. CoRR (2022)
Nan Lu, Zhao Wang, Xiaoxiao Li, Gang Niu, Qi Dou, Masashi Sugiyama
Federated Learning from Only Unlabeled Data with Class-Conditional-Sharing Clients. CoRR (2022)

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Publication Activity (10 Years)

Top Topics

Top Venues

Masashi Sugiyama