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 Conference Papers (Available on Advance Programs)  (Sort by: Date Descending)
 Results 1 - 13 of 13  /   
Committee Date Time Place Paper Title / Authors Abstract Paper #
DC 2024-02-28
15:05
Tokyo Kikai-Shinko-Kaikan Bldg. Locating High Power Consuming Area by Topology Analysis for Logic Circuit
Tomoya Yamashita, Kohei Miyase, Xiaoqing Wen (Kyutech) DC2023-101
(To be available after the conference date) [more] DC2023-101
pp.41-46
NLP, MSS 2023-03-17
14:30
Nagasaki
(Primary: On-site, Secondary: Online)
Global Convergence Analysis of Distributed HALS Algorithm for Nonnegative Matrix Factorization
Keiju Hayashi, Tsuyoshi Migita, Norikazu Takahashi (Okayama Univ.) MSS2022-104 NLP2022-149
As a fast computational method for Nonnegative Matrix Factorization (NMF),
the Hierarchical Alternating Least Squares ... [more]
MSS2022-104 NLP2022-149
pp.198-203
IMQ 2018-12-21
16:30
Tokyo Katsushika Campus, Tokyo University of Science Analysis of accommodation response and convergence eye movement when viewing 8K images
Reiko Koyama, Shinya Mochiduki, Mitsuho Yamada (Tokai Univ) IMQ2018-22
In recent years, 4K and 8K display have become widespread. The 8K displays have 4 times the pixel of the 4K displays, he... [more] IMQ2018-22
pp.39-42
CAS, NLP 2018-10-19
14:45
Miyagi Tohoku Univ. Convergence of a Pseudo-Decentralized Discrete-Time Algorithm for Computing Algebraic Connectivity -- Analysis of the Case Where Algebraic Connectivity is Repeated --
Tomohisa Urakami, Norikazu Takahashi (Okayama Univ.) CAS2018-58 NLP2018-93
The algebraic connectivity of a network, which is defined as the second smallest eigenvalue of the Laplacian matrix, is ... [more] CAS2018-58 NLP2018-93
pp.115-120
IT, SIP, RCS 2017-01-20
10:50
Osaka Osaka City Univ. A New Iterative Method for Nonnegative Matrix Factorization with Sparsity and Smoothness and Its Global Convergence
Takumi Kimura, Norikazu Takahashi (Okayama Univ.) IT2016-93 SIP2016-131 RCS2016-283
Nonnegative Matrix Factorization (NMF) is an operation that decomposes a given nonnegative matrix into two nonnegative f... [more] IT2016-93 SIP2016-131 RCS2016-283
pp.273-278
CQ, IMQ, MVE, IE
(Joint) [detail]
2015-03-04
11:35
Tokyo Seikei Univ. Eye movement while viewing several resolution and diaphragm values images
Hideaki Takahira, Shinya Mochiduki, Yumeko Yamazaki, Mitsuho Yamada (Tokai Univ.) IMQ2014-56 IE2014-117 MVE2014-104
The spread of super-high-definition image is advanced, and viewers will notice strong feelings of presence and of the vi... [more] IMQ2014-56 IE2014-117 MVE2014-104
pp.137-142
CAS, SIP, MSS, VLD, SIS [detail] 2014-07-11
16:40
Hokkaido Hokkaido University Derivation of New Update Rules based on KL, Gamma, Renyi Divergences for Nonnegative Matrix Factorization
Masato Seki, Norikazu Takahashi (Okayama Univ) CAS2014-47 VLD2014-56 SIP2014-68 MSS2014-47 SIS2014-47
Three new update rules based on Kullback-Leibler divergence, gamma-divergence and Renyi divergence for nonnegative matr... [more] CAS2014-47 VLD2014-56 SIP2014-68 MSS2014-47 SIS2014-47
pp.253-258
EA, SP, SIP 2012-05-24
16:00
Osaka Osaka Univ. Nakanoshima Center Convergence Values of an NLMS Algorithm for Sinusoids With Rational Number Period
Yuki Satomi, Arata Kawamura, Youji Iiguni (Osaka Univ.) EA2012-20 SIP2012-20 SP2012-20
In an adaptive system identification filter with a stochastic input signal,a coefficient vector updated with the NLMS al... [more] EA2012-20 SIP2012-20 SP2012-20
pp.115-120
CS, SIP, CAS 2011-03-03
10:00
Okinawa Ohhamanobumoto memorial hall (Ishigaki)( Two improvements of the fast iterative shrinkage/thresholding algorithm -- Overrelaxation and weak convergence --
Masao Yamagishi, Isao Yamada (Tokyo Inst. of Tech) CAS2010-126 SIP2010-142 CS2010-96
In this paper, we present two improved schemes of FISTA (an iterative gradient-based algorithm, whose convergence rate o... [more] CAS2010-126 SIP2010-142 CS2010-96
pp.143-148
IBISML, PRMU, IPSJ-CVIM [detail] 2010-09-06
11:40
Fukuoka Fukuoka Univ. Evaluation of the error rate of the classifier under the margin assumption
Takanori Ayano, Joe Suzuki (Osaka Univ) PRMU2010-82 IBISML2010-54
In statistical learning, it is very important for evaluation of the performance of SVM and the conclusion of the difficu... [more] PRMU2010-82 IBISML2010-54
pp.193-199
SIP, IE 2008-04-17
15:45
Tokyo Kikai-Shinko-Kaikan Bldg. A Study on Adaptive Recursive Filter Based on Lagrange-White's Algorithm
Masaki Kobayashi, Chi Wang (Chubu Univ.) SIP2008-12 IE2008-12
In this paper, we propose a new adaptive recursive filter that has innovated the Lagrange multiplier method into
the ad... [more]
SIP2008-12 IE2008-12
pp.67-72
IT 2008-01-17
15:15
Tokyo Waseda Univ. A Scheme to Reduce the Calculation Cost of the Sum-Product Decoding
Rumi Aoyama, Yuichi Kaji (NAIST) IT2007-28
This paper investigates a modified sum-product decoding algorithm which suspends updating reliable messages obtained dur... [more] IT2007-28
pp.19-24
PRMU 2007-12-13
09:30
Hyogo Kobe Univ. Comparison of Eigenvalue Computation Speed for Time-Varying Large-Size Symmetric Matrices
Hiroyuki Taira, Kenichi Kanatani (Okayama Univ.) PRMU2007-135
We study iterative schemes for computing the largest eigenvalue and the
corresponding eigenvector of a time-varying lar... [more]
PRMU2007-135
pp.1-6
 Results 1 - 13 of 13  /   
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