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All Technical Committee Conferences (Searched in: All Years)
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Search Results: Conference Papers |
Conference Papers (Available on Advance Programs) (Sort by: Date Descending) |
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Committee |
Date Time |
Place |
Paper Title / Authors |
Abstract |
Paper # |
PRMU, IBISML, IPSJ-CVIM |
2024-03-04 10:40 |
Hiroshima |
Hiroshima Univ. Higashi-Hiroshima campus (Primary: On-site, Secondary: Online) |
Poisoning Attack on Fairness of Fair Classification Algorithm through Threshold Control Dai Shengtian, Akimoto Youhei (Univ. of Tsukuba/RIKEN), Jun Sakuma (Tokyo Tech./RIKEN), Fukuchi Kazuto (Univ. of Tsukuba/RIKEN) IBISML2023-47 |
The ethical issues of artificial intelligence have become more severe as machine learning is widely used in several fiel... [more] |
IBISML2023-47 pp.49-56 |
IBISML |
2022-12-23 10:00 |
Kyoto |
Kyoto University (Primary: On-site, Secondary: Online) |
Zero-shot domain adaptation based on dual-level mix and contrast Yu Zhe, Fukuchi Kazuto, Sakuma Jun (Tsukuba Univ/Riken AIP) IBISML2022-53 |
[more] |
IBISML2022-53 pp.70-77 |
IBISML |
2022-01-17 11:20 |
Online |
Online |
CAMRI Loss: Class-wise Additive Angular Margin Loss for Improving Recall of a Specific Class Daiki Nishiyama (Univ. Tsukuba), Fukuchi Kazuto, Yohei Akimoto, Jun Sakuma (Univ. Tsukuba/RIKEN) IBISML2021-22 |
In real-world applications of multiclass classification models, there is a need to increase the recall of classes where ... [more] |
IBISML2021-22 pp.29-36 |
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 |
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