文献
J-GLOBAL ID:201702221729065047
整理番号:17A0473811
効率的な局所性はグラフに基づく学習のためのスパース表現を強調【Powered by NICT】
Efficient locality weighted sparse representation for graph-based learning
著者 (4件):
Feng Xiaodong
(School of Political Science and Public Administration, University of Electronic Science and Technology of China, Chengdu, Sichuan 611731, China)
,
Wu Sen
(Donlinks School of Economics and Management, University of Science and Technology Beijing, Beijing 100083, China)
,
Zhou Wenjun
(Business Analytics and Statistics, University of Tennessee, Knoxville, TN 37996, USA)
,
Quan Min
(Donlinks School of Economics and Management, University of Science and Technology Beijing, Beijing 100083, China)
資料名:
Knowledge-Based Systems
(Knowledge-Based Systems)
巻:
121
ページ:
129-141
発行年:
2017年
JST資料番号:
T0426A
ISSN:
0950-7051
資料種別:
逐次刊行物 (A)
記事区分:
原著論文
発行国:
オランダ (NLD)
言語:
英語 (EN)