RIKEN Center for Advanced Intelligence Project Imperfect Information Learning Team

Team Leader: Masashi Sugiyama (D.Eng.)

Japanese Page

Research Summary

Recently, machine learning technology with big data has been actively investigated and its effectiveness has been demonstrated. However, depending on application domains, it is difficult or even it is not possible to collect a large amount of data. In the Imperfect Information Learning Team, for various machine learning tasks including supervised learning, unsupervised learning, and reinforcement learning, we develop novel algorithms that allow accurate learning from limited information. We also elucidate their theoretical properties and apply them to various real-world applications ranging from fundamental science to business.

Research Subjects:

Development of machine learning algorithms from imperfect information
Theoretical analysis of machine learning algorithms
Real-world application of machine learning algorithms

Main Research Fields

Informatics

Related Research Fields

Intelligent informatics
Perceptual information processing
Statistical science

Keywords

artificial intelligence
machine learning
weakly supervised learning
reinforcement learning
deep learning

Selected Publications

1. Zhang, J., Xu, X., Han, B., Niu, G., Cui, L., Sugiyama, M., & Kankanhalli, M.:
"Attacks which do not kill training make adversarial learning stronger."
In Proceedings of 37th International Conference on Machine Learning (ICML2020), to appear.
2. Tangkaratt, V., Han, B., Khan, M. E., & Sugiyama, M.:
"Variational imitation learning with diverse-quality demonstrations."
In Proceedings of 37th International Conference on Machine Learning (ICML2020), to appear.
3. Han, B., Niu, G., Yu, X., Yao, Q., Xu, M., Tsang, I., & Sugiyama, M.:
"SIGUA: Forgetting may make learning with noisy labels more robust."
In Proceedings of 37th International Conference on Machine Learning (ICML2020), to appear.
4. Feng, L., Kaneko, T., Han, B., Niu, G., An, B., & Sugiyama, M.:
"Learning with multiple complementary labels."
In Proceedings of 37th International Conference on Machine Learning (ICML2020), to appear.
5. Chou, Y.-T., Niu, G., Lin, H.-T., & Sugiyama, M.:
"Unbiased risk estimators can mislead: A case study of learning with complementary labels."
In Proceedings of 37th International Conference on Machine Learning (ICML2020), to appear.
6. Lv, J., Xu, M., Feng, L., Niu, G., Geng, X., & Sugiyama, M.:
"Progressive identification of true labels for partial-label learning."
In Proceedings of 37th International Conference on Machine Learning (ICML2020), to appear.
7. Ishida, T., Yamane, I., Sakai, T., Niu, G., & Sugiyama, M.:
"Do we need zero training loss after achieving zero training error?"
In Proceedings of 37th International Conference on Machine Learning (ICML2020), to appear.
8. Lu, N., Zhang, T., Niu, G., & Sugiyama, M.:
Mitigating overfitting in supervised classification from two "unlabeled datasets: A consistent risk correction approach."
In Proceedings of 23rd International Conference on Artificial Intelligence and Statistics (AISTATS2020), pp.1115-1125, 2020.
9. Xia, X., Liu, T., Wang, N., Han, B., Gong, C., Niu, G., & Sugiyama, M.:
"Are anchor points really indispensable in label-noise learning?"
In Advances in Neural Information Processing Systems 32 (NeurIPS2019), pp.6835-6846, 2019.
10. Wu, Y.-H., Charoenphakdee, N., Bao, H., Tangkaratt, V., & Sugiyama, M.:
"Imitation learning from imperfect demonstration."
In Proceedings of 36th International Conference on Machine Learning (ICML2019), pp.6818-6827, 2019.

Recent Research Results

Nov. 26, 2018
Smarter AI: machine learning without negative data

Lab Members

Principal investigator

Masashi Sugiyama: Team Leader

Core members

Gang Niu: Research Scientist
Shuo Chen: Postdoctoral Researcher
Jingfeng Zhang: Postdoctoral Researcher
Jiaqi Lyu: Postdoctoral Researcher
Shinichi Nakajima: Senior Visiting Scientist
Florian Baptiste Yger: Visiting Scientist
Takashi Ishida: Visiting Scientist
Miao Xu: Visiting Scientist
Bo Han: Visiting Scientist
Feng Liu: Visiting Scientist
Tongliang Liu: Visiting Scientist
Lei Feng: Visiting Scientist
Takahiro Mimori: Visiting Scientist
Takayuki Osa: Visiting Scientist
Futoshi Futami: Visiting Scientist
Yifan Zhang: Research Part-time Worker I
Masahiro Fujisawa: Research Part-time Worker I

Careers

Position	Deadline
Seeking a Research Scientist or Postdoctoral Researcher (W22343)	Open until filled

Contact Information

Nihonbashi 1-chome Mitsui Building, 15th floor,
1-4-1 Nihonbashi,
Chuo-ku, Tokyo
103-0027, Japan
Email: masashi.sugiyama [at] riken.jp