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Technical Committee on Information-Based Induction Sciences and Machine Learning (IBISML) (Searched in: 2020)
Search Results: Keywords 'from:2020-10-20 to:2020-10-20'
| Committee | Date Time | Place | Paper Title / Authors | Abstract | Paper # | |
| IBISML | 2020-10-22 10:25 |
Online | Online |  IBISML2020-28 |
I will introduce significant pattern mining techniques that are designed to find statistically significant interactions ... [more] | IBISML2020-28 p.47 |
| IBISML | 2020-10-22 11:15 |
Online | Online | IBISML2020-29 |
[more] | IBISML2020-29 p.48 |
| IBISML | 2020-10-22 11:55 |
Online | Online | [more] | ||
| IBISML | 2020-10-22 14:00 |
Online | Online | An Extended LiNGAM minimizing Mutual Information and its Application to Ordering Discrete Variables Joe Suzuki, Yusuke Inaoka (OU) IBISML2020-30 |
[more] | IBISML2020-30 pp.49-54 |
| IBISML | 2020-10-22 14:25 |
Online | Online | Improvement of the robustness by increasing the size of feedback vertex set Masaki Chujyo, Yukio Hayashi (JAIST) IBISML2020-31 |
Many real world networks such as power grid and communication networks are commonly scale-free, but highly vulnerable ag... [more] | IBISML2020-31 pp.55-60 |
| IBISML | 2020-10-22 14:50 |
Online | Online | Suppressing explanations with irrelevant concepts in deep learning Munemasa Tomohiro (Tsukuba Univ), Fukuchi Kazuto, Akimoto Yohei, Sakuma Jun (Tsukuba Univ/Riken AIP) IBISML2020-32 |
TCAV [1], which is an explanation method using a concept that humans easily understand for deep learning models, concept... [more] | IBISML2020-32 pp.61-68 |
| IBISML | 2020-10-22 15:15 |
Online | Online | A Proximal Gradient Method for Convex Clustering Ryosuke Shimmura, Joe Suzuki (Osaka Univ.) IBISML2020-33 |
(To be available after the conference date) [more] | IBISML2020-33 pp.69-74 |
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