| IEICE Technical Committee Submission System Conference Schedule |
Online Proceedings [Sign in] Tech. Rep. Archives |
All Technical Committee Conferences (Searched in: All Years)
| Committee | Date Time | Place | Paper Title / Authors | Abstract | Paper # | |
| NC, MBE | 2015-03-17 13:00 |
Tokyo | Tamagawa University | Latent dynamics estimation from time-series spectral data Shin Murata, Kenji Nagata (Univ. of Tokyo), Makoto Uemura (Hiroshima Univ.), Masato Okada (Univ. of Tokyo/RIKEN)  MBE2014-173 NC2014-124 |
Estimation of latent dynamics from time-series data is important problem in a broad range of fields. In this research, w... [more] | MBE2014-173 NC2014-124 pp.319-324 |
| NC, MBE | 2015-03-17 13:25 |
Tokyo | Tamagawa University | Effects of downsampling on hyperparameter estimation for Markov random field model Hirotaka Sakamoto (Univ. Tokyo), Yoshinori Nakanishi-Ohno (Univ. Tokyo/JSPS), Masato Okada (Univ. Tokyo/RIKEN) MBE2014-174 NC2014-125 |
We investigate effects which downsampling has on latent-variable estimation from image data. Downsampling is essential f... [more] | MBE2014-174 NC2014-125 pp.325-330 |
| IBISML | 2014-11-17 17:00 |
Aichi | Nagoya Univ. | [Poster Presentation]
Statistical mechanical analysis of lossy compression by overcomplete basis Yoshinori Nakanishi-Ohno (Univ. Tokyo), Tomoyuki Obuchi (Tokyo Tech), Masato Okada (Univ. Tokyo), Yoshiyuki Kabashima (Tokyo Tech) IBISML2014-50 |
Information processing using the sparsity of information has been actively studied such as compressed sensing. In this ... [more] |
IBISML2014-50 pp.119-126 |
| NC, MBE (Joint) |
2014-03-18 10:20 |
Tokyo | Tamagawa University | Theory of firing distribution with common noise originating from synaptic connectivity Ryo Karakida, Yasuhiko Igarashi, Kenji Nagata (Univ. of Tokyo), Masato Okada (Univ. Tokyo/RIKEN) NC2013-103 |
Common noise is a correlated noise input shared by multiple neurons. Biological experiments have shown that the common n... [more] | NC2013-103 pp.85-90 |
| NC, MBE (Joint) |
2014-03-18 11:00 |
Tokyo | Tamagawa University | Active memory capacity in a neural network with short-term synaptic plasticity Kenji Tanaka (Univ. of Tokyo), Yasuhiko Igarashi (Univ. of Tokyo/JSPS), Masato Okada (Univ. of Tokyo/RIKEN) NC2013-105 |
In pre-frontal cortex (PFC), electro physiological experiments studies have established a link between the neuronal acti... [more] | NC2013-105 pp.97-102 |
| NC, MBE (Joint) |
2014-03-18 13:00 |
Tokyo | Tamagawa University | Model selection of NiGa_2S_4 triangular lattice by Bayesian estimation Hikaru Takenaka, Kenji Nagata, Takashi Mizokawa (Univ. of Tokyo), Masato Okada (Univ. of Tokyo/RIKEN) NC2013-107 |
The superexchange interaction, which favors parallel or anti-parallel alignment of electron spins in magnets, has an imp... [more] | NC2013-107 pp.109-114 |
| NC, MBE (Joint) |
2014-03-18 13:20 |
Tokyo | Tamagawa University | Bayesian estimation for spectral deconvolution and estimation for limit of measurement time Kenji Nagata, Rei Muraoka, Takehiko Sasaki, Masato Okada (Univ. of Tokyo) NC2013-108 |
[more] | NC2013-108 pp.115-120 |
| NC, MBE (Joint) |
2014-03-18 13:40 |
Tokyo | Tamagawa University | Computational validation of the information criterion WBIC by the exchange Monte Carlo method Satoru Tokuda, Kenji Nagata (Univ. of Tokyo), Sumio Watanabe (Tokyo Inst. of Tech.), Masato Okada (Univ. of Tokyo/RIKEN) NC2013-109 |
In the models with hierarchy like artificial neural networks and mixture models, asymptotic normality, which AIC and BIC... [more] | NC2013-109 pp.121-126 |
| NC, MBE (Joint) |
2013-11-22 13:00 |
Miyagi | Tohoku University | Statistical Mechanics of Neural Network Model with Sparse and Local Excitation Akira Manda, Jun Kitazono (Univ. of Tokyo), Toshiaki Omori (Kobe Univ.), Masato Okada (Univ. of Tokyo/RIKEN BSI) NC2013-46 |
[more] | NC2013-46 pp.1-6 |
| NC, MBE (Joint) |
2013-11-22 14:15 |
Miyagi | Tohoku University | Verification of Effectiveness of the Probabilistic Algorithm for Latent Structure Extraction Using Associative Memory Model Kensuke Wakasugi (Univ. Tokyo), Tatsu Kuwatani (Tohoku Univ.), Kenji Nagata (Univ. Tokyo), Hideki Asoh (AIST), Masato Okada (Univ. Tokyo/RIKEN) NC2013-49 |
There are many analysis methods for high-dimensional data, but, in many cases, analysis is done under assumption that a ... [more] | NC2013-49 pp.17-22 |
| IBISML | 2013-11-13 15:45 |
Tokyo | Tokyo Institute of Technology, Kuramae-Kaikan | [Poster Presentation]
Efficient Exhaustive Search for Variable Selection with Exchange Monte Carlo Method Kenji Nagata (Univ. of Tokyo), Jun Kitazono (JST), Shinichi Nakajima (Nikon), Satoshi Eifuku (Fukushima Medical Univ.), Ryoi Tamura (Univ. of Toyama), Masato Okada (Univ. of Tokyo) IBISML2013-61 |
[more] | IBISML2013-61 pp.191-196 |
| NC, MBE (Joint) |
2013-07-19 14:30 |
Tokushima | The University of Tokushima | Statistical Mechanics of node-perturbation Learning using two independent noises Kazuyuki Hara (Nihon Univ.), Kentaro Katahira, Masato Okada (Univ. of Tokyo) NC2013-17 |
Node perturbation learning is a stochastic gradient descent method for neural networks. It estimates the gradient by com... [more] | NC2013-17 pp.13-18 |
| MBE, NC (Joint) |
2013-03-13 14:35 |
Tokyo | Tamagawa University | Hebbian learning of transition probabilities
-- a neural network study -- Hiroshi Saito, Ken Takiyama (Univ. of Tokyo), Masato Okada (Univ. of Tokyo/RIKEN) NC2012-145 |
State of the environment changes on and on, and humans animals predict future state through their experiences. Recent br... [more] | NC2012-145 pp.67-72 |
| NC, MBE (Joint) |
2012-12-12 10:40 |
Aichi | Toyohashi University of Technology | A numerical derivation of learning coefficient in radial basis function network Satoru Tokuda, Kenji Nagata, Masato Okada (Univ. of Tokyo) NC2012-78 |
Radial basis function (RBF) network is a regression model which regresses input-output data by radial basis functions su... [more] | NC2012-78 pp.25-30 |
| NC, MBE (Joint) |
2012-12-12 11:05 |
Aichi | Toyohashi University of Technology | Instabilities of spurious state with synaptic depression Shin Murata, Yosuke Otsubo, Kenji Nagata (Univ. of Tokyo), Masato Okada (Univ. of Tokyo/BSI RIKEN) NC2012-79 |
The associative memory model is one of typical neural network model and has equilibrium state called spurious state in w... [more] | NC2012-79 pp.31-36 |
| NC, MBE (Joint) |
2012-12-12 15:40 |
Aichi | Toyohashi University of Technology | Distribution estimation of hyperparameters in Markov random field model Yoshinori Ohno, Kenji Nagata (Univ. Tokyo), Hayaru Shouno (UEC), Masato Okada (Univ. Tokyo/RIKEN) NC2012-86 |
Recent advances in measurement techniques allow us to obtain a large quantity of imaging data in various natural science... [more] | NC2012-86 pp.55-60 |
| NC, MBE (Joint) |
2012-12-12 16:05 |
Aichi | Toyohashi University of Technology | Sparse Estimation of Spike-Triggered Average Shimpei Yotsukura (Univ. of Tokyo), Toshiaki Omori (Kobe Univ.), Kenji Nagata, Masato Okada (Univ. of Tokyo) NC2012-87 |
Spike triggered average (STA) and phase response curve characterize response properties of single neurons. A recent theo... [more] | NC2012-87 pp.61-66 |
| MBE, NC (Joint) |
2012-11-17 13:55 |
Miyagi | Tohoku University | Inter-layer correlation in a feed-forward network with intra-layer common noise Ryo Karakida, Yasuhiko Igarashi (Univ. of Tokyo), Kenji Nagata (Univ. Tokyo), Masato Okada (Univ. Tokyo/RIKEN) NC2012-69 |
Intra-layer common noise leads to the synchronous firing of neurons in a feed-forward network. The synchronous firing ... [more] |
NC2012-69 pp.45-50 |
| IBISML | 2012-11-08 15:00 |
Tokyo | Bunkyo School Building, Tokyo Campus, Tsukuba Univ. | Replica analysis of CDMA multiuser detection with M-ary phase-shift keying Hiroyuki Kato (Kansai Univ.), Masato Okada (Univ. of Tokyo/RIKEN), Seiji Miyoshi (Kansai Univ.) IBISML2012-85 |
Code Division Multiple Access (CDMA) is a technique for multiple access, and used for mobile phone,satellite communicati... [more] | IBISML2012-85 pp.367-372 |
| PRMU, IBISML, IPSJ-CVIM (Joint) [detail] |
2012-09-03 10:30 |
Tokyo | Nonparametric Bayesian Estimation for Automatic Image Annotation Using Gaussian Mixture Model Yukihiro Tsuboshita, Noriji Kato (Fuji Xerox), Masato Okada (The universisty of Tokyo) PRMU2012-40 IBISML2012-23 |
Automatic image annotation (AIA) is a process to automatically assign metadata to a digital image in the form of caption... [more] | PRMU2012-40 IBISML2012-23 pp.93-98 |
|
[Return to Top Page]