Computation, Structure, and Learning
Machine learning is the discipline of studying intelligent computing systems, which nowadays plays a key role in artificial intelligence (AI). To reveal the nature of learning, we focus on the relationship between computational processes, discrete structures, and machine learning models.
- Kazu Ghalamkari, Ryuichi Kanoh, and Yuhi Kawakami joined our lab as new Ph.D. students (Apr. 1, 2020).
- Ian Andrew Walker joined our lab as an internship student (Jan. 14, 2020).
- Assoc. Prof. Sugiyama will give a lecture about "Mechanisms of Machine Learning" at National Institute of Technology, Kurume College (Dec. 6, 2019). [Slide] (in Japanese)
- Assoc. Prof. Sugiyama will give a talk about "Learning with Incidence Algebra and Dually Flat Structure" at IBIS 2019 (Nov. 20, 2019). [Slide]
- Prasad Cheema joined our lab as an internship student (Nov. 18, 2019).
- Masatsugu Yamada joined our lab as a new Ph.D. student (Oct. 7, 2019).
- Assoc. Prof. Sugiyama has been awarded "Reviewer Award" of the ECMLPKDD 2019 Journal Track (Sep. 12, 2019).
- Assoc. Prof. Sugiyama will organize the session "Machine Learning and Discrete Mathematics" at IBIS 2019 (Nov. 20-23, 2019). All slides are available at the IBIS 2019 website.
- Assoc. Prof. Sugiyama has presented the work "Finding Statistically Significant Interactions between Continuous Features" at IJCAI 2019 (Aug. 10-16, 2019). [Paper] [Slide] [Poster]
- The lab webpage has been released (Jul. 4, 2019).
National Institute of Informatics,
2-1-2 Hitotsubashi, Chiyoda-ku, Tokyo 101-8430, Japan
Email: mahito (at) nii.ac.jp