文献
J-GLOBAL ID:202002291548609248
整理番号:20A2046592
形状レットベースのマルチインスタンス学習のための理論とアルゴリズム【JST・京大機械翻訳】
Theory and Algorithms for Shapelet-Based Multiple-Instance Learning
著者 (6件):
Suehiro Daiki
(Department of Advanced Information Technology, Faculty of Information Science and Electrical Engineering, Kyushu University, and RIKEN Center for Advanced Intelligence Project, Nishi-ku, Fukuoka, 8190395, Japan)
,
Hatano Kohei
(Faculty of Arts and Science, Kyushu University, and RIKEN Center for Advanced Intelligence Project, Nishi-ku, Fukuoka, 8190395, Japan)
,
Takimoto Eiji
(Department of Informatics, Faculty of Information Science and Electrical Engineering, Kyushu University, Nishi-ku, Fukuoka, 8190395, Japan)
,
Yamamoto Shuji
(Department of Mathematics, Keio University, and RIKEN Center for Advanced Intelligence Project, Minatokita-ku, Yokohama, 2238522, Japan)
,
Bannai Kenichi
(Department of Mathematics, Keio University, and RIKEN Center for Advanced Intelligence Project, Minatokita-ku, Yokohama, 2238522, Japan)
,
Takeda Akiko
(Department of Creative Informatics, University of Tokyo, and RIKEN Center for Advanced Intelligence Project, Bunkyo-ku, Tokyo, 1138656, Japan)
資料名:
Neural Computation
(Neural Computation)
巻:
32
号:
8
ページ:
1580-1613
発行年:
2020年
JST資料番号:
W0257A
ISSN:
0899-7667
資料種別:
逐次刊行物 (A)
記事区分:
原著論文
発行国:
アメリカ合衆国 (USA)
言語:
英語 (EN)