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 Conference Papers (Available on Advance Programs)  (Sort by: Date Descending)
 Results 1 - 12 of 12  /   
Committee Date Time Place Paper Title / Authors Abstract Paper #
MBE, NC 2022-12-03
10:20
Osaka Osaka Electro-Communication University ICA with SCAD penalty via DC algorithm
Yusuke Endo, Koujin Takeda (Ibaraki Univ.) MBE2022-31 NC2022-53
In this work, we propose an improved method of ICA(Independent Component Analysis), which is used for identifying latent... [more] MBE2022-31 NC2022-53
pp.38-42
NC, MBE
(Joint)
2020-03-05
16:10
Tokyo University of Electro Communications
(Cancelled but technical report was issued)
Improvement of neuronal ensemble inference by Monte Carlo method and applying to real data
Shun Kimura, Koujin Takeda (Ibaraki Univ.), Keisuke Ota (Riken) NC2019-101
In this work, we propose an improved inference algorithm for neuronal ensembles, which can classify neurons into ensembl... [more] NC2019-101
pp.149-154
IBISML 2018-11-05
15:10
Hokkaido Hokkaido Citizens Activites Center (Kaderu 2.7) [Poster Presentation] Analysis of matrix factorization dynamics from variational Bayes solution
Tomoki Tamai, Koujin Takeda (Ibaraki Univ.) IBISML2018-74
(Advance abstract in Japanese is available) [more] IBISML2018-74
pp.227-231
IBISML 2017-11-10
13:00
Tokyo Univ. of Tokyo [Poster Presentation] Improvement of learning method with convolutional restricted Boltzmann machine based on PCD
Ryosuke Ishi, Reiki Suda, Koujin Takeda (Ibaraki Univ.) IBISML2017-68
 [more] IBISML2017-68
pp.251-254
IBISML 2017-11-10
13:00
Tokyo Univ. of Tokyo [Poster Presentation] Variational Bayes method for matrix factorization to two sparse factorized matrices
Tomoki Tamai, Koujin Takeda (Ibaraki Univ.) IBISML2017-75
 [more] IBISML2017-75
pp.297-300
IBISML 2016-11-16
15:00
Kyoto Kyoto Univ. [Poster Presentation] Approximate Method of Variational Bayesian Matrix Completion with Sparse Prior
Ryota Kawasumi, Koujin Takeda (Ibaraki Univ) IBISML2016-62
 [more] IBISML2016-62
pp.117-121
IBISML 2014-11-17
17:00
Aichi Nagoya Univ. [Poster Presentation] Application of partial parallel interference cancellation to sparse signal recovery
Koujin Takeda (Ibaraki Univ.), Toshiyuki Tanaka (Kyoto Univ.) IBISML2014-35
We apply partial parallel interference cancellation scheme in CDMA demodulation to sparse signal recovery in compressed ... [more] IBISML2014-35
pp.1-7
IBISML 2014-11-17
17:00
Aichi Nagoya Univ. [Poster Presentation] Feature Extraction for Image Classification using Restricted Boltzmann Machines
Reiki Suda, Koujin Takeda (Ibaraki Univ.) IBISML2014-36
Learning restricted Boltzmann machines (RBMs) for high-dimensional data using maximum likelihood estimation had been fac... [more] IBISML2014-36
pp.9-15
IBISML 2012-11-08
15:00
Tokyo Bunkyo School Building, Tokyo Campus, Tsukuba Univ. Recovery algorithm in compressed sensing based on maximum a posteriori estimation
Koujin Takeda, Yoshiyuki Kabashima (Tokyo Tech.) IBISML2012-76
We propose an idea for how to derive sparse data recovery algorithm with smaller computational cost in compressed sensin... [more] IBISML2012-76
pp.297-302
IBISML 2011-11-09
15:45
Nara Nara Womens Univ. Replica Symmetry Breaking in Compressed Sensing
Koujin Takeda, Yoshiyuki Kabashima (Tokyo Tech.) IBISML2011-60
In our preceding works, we provided a general framework for estimating the reconstruction limit in compressed sensing by... [more] IBISML2011-60
pp.123-126
IBISML 2010-11-05
15:30
Tokyo IIS, Univ. of Tokyo [Poster Presentation] Performance analysis of compressed sensing under correlated signals
Koujin Takeda, Yoshiyuki Kabashima (Tokyo Tech.) IBISML2010-83
We provide a scheme for exploring the reconstruction limit of compressed sensing by minimizing the general cost function... [more] IBISML2010-83
pp.175-180
IBISML 2010-11-05
15:30
Tokyo IIS, Univ. of Tokyo [Poster Presentation] Statistical mechanical analysis of hierarchical random code ensemble in signal processing
Koujin Takeda (Tokyo Tech.), Tomoyuki Obuchi (Osaka Univ.), Kazutaka Takahashi (Tokyo Tech.) IBISML2010-90
The relation between signal processing in information science and statistical physics has been intensively discussed. In... [more] IBISML2010-90
pp.231-238
 Results 1 - 12 of 12  /   
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