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Committee Date Time Place Paper Title / Authors Abstract Paper #
NLP, CAS 2023-10-07
13:20		 Gifu Work plaza Gifu Proposal and evaluation of a distributed lasso algorithm based on alternating direction multiplier method
Naoki Toda, Tsuyoshi Migita, Norikazu Takahashi (Okayama Univ.) CAS2023-55 NLP2023-54		 Lasso is widely known as a sparse estimation method for regression coefficients in linear regression models, and the Alt... [more] CAS2023-55 NLP2023-54
pp.111-116
IBISML 2012-11-07
15:30		 Tokyo Bunkyo School Building, Tokyo Campus, Tsukuba Univ. Structure Learning for Anomaly Localization
Satoshi Hara, Takashi Washio (Osaka Univ.) IBISML2012-36		 In this paper, we propose a graphical model learning algorithm for an anomaly localization. We introduce a new regulariz... [more] IBISML2012-36
pp.17-22
CAS, CS, SIP 2012-03-08
14:10		 Niigata The University of Niigata Three variants of alternating direction method of multipliers without certain inner iterations and their application to image super-resolution via sparse representation
Masao Yamagishi, Shunsuke Ono, Isao Yamada (Tokyo Inst. of Tech.) CAS2011-115 SIP2011-135 CS2011-107		 We propose three variants of Alternating Direction Method of Multipliers (ADMM) employing simplified updates under addit... [more] CAS2011-115 SIP2011-135 CS2011-107
pp.49-54
SIP, RCS 2011-01-20
15:20		 Kagoshima   Generalizing the multiple measurement setting from sparse vector recovery to low-rank matrix recovery
Silvia Gandy, Isao Yamada (Tokyo Inst. of Tech.) SIP2010-92 RCS2010-222		 We discuss a novel multiple measurement setting for low-rank matrix recovery in analogy to the approach taken in the spa... [more] SIP2010-92 RCS2010-222
pp.137-142
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