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Committee Date Time Place Paper Title / Authors Abstract Paper #
IBISML 2016-03-18
10:00		 Tokyo Institute of Statistical Mathematics An Efficient Tensor Spectral Algorithm for Learning Rank Deficient Co-cluster Structure from Large Scale Relational Data
Hideo Umetani, Iku Ohama (Panasonic Co., Ltd) IBISML2015-99		 The Stochastic Block Model (SBM) is a well-known relational model for discovering co-cluster structure from relational d... [more] IBISML2015-99
pp.39-46
PRMU, IBISML, IPSJ-CVIM [detail] 2014-09-02
15:15		 Ibaraki   On Improvement of Tensor Spectral Method for Estimation of Mixed Membership Stochastic Block Model
Wataru Kaigaishi (Univ. of Tokyo), Hisashi Kashima (Kyoto Univ.) PRMU2014-51 IBISML2014-32		 Maximum likelihood estimation is a common approach to estimating mixed membership stochastic block models; however, it i... [more] PRMU2014-51 IBISML2014-32
pp.131-136
PRMU 2013-03-15
11:15		 Tokyo   Recognition of Block World from Monocular Single Image Considering Spatial Relationship between Blocks
Daichi Tanii, Hotaka Takizawa (Univ. of Tsukuba) PRMU2012-213		 In this report, we propose a method of recognizing block scenes from monocular images. Block-like objects are represente... [more] PRMU2012-213
pp.199-204
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