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 Conference Papers (Available on Advance Programs)  (Sort by: Date Descending)
 Results 1 - 20 of 43  /  [Next]  
Committee Date Time Place Paper Title / Authors Abstract Paper #
NLP, MSS
(Joint)
2019-03-14
15:10
Fukui Bunkyo Camp., Univ. of Fukui Automatic classification of human behavior using wearable devices
Keita Sato, Masafumi Chida, Yoshihiro Hayakawa, Nahomi Fujiki (NITS) NLP2018-129
(To be available after the conference date) [more] NLP2018-129
pp.27-30
NLP 2016-12-12
16:25
Aichi Chukyo Univ. The Relationship between Modular Neural Network and Noise Effect
Kou Muraoka, Rui Yoshida, Yoshihiro Hayakawa (NIT, Sendai) NLP2016-91
Some of combinatorial optimization problems have problems that the number of solutions to be searched increases with the... [more] NLP2016-91
pp.39-44
NLP 2016-03-25
11:30
Kyoto Kyoto Sangyo Univ. Image Feature Extraction based on Neural Network and Its Application
Yoshihiro Hayakawa, Takanori Oonuma, Hideyuki Kobayashi, Akiko Takahashi, Shinji Chiba, Nahomi Fujiki (NIT, Sendai) NLP2015-153
 [more] NLP2015-153
pp.63-67
NLP, CCS 2015-06-12
10:15
Tokyo Waseda Univerisity Dynamics analysis of Modular Neural Network using Toy Model
Yoshihiro Hayakawa, Masayuki Matumori (NIT,Sendai) NLP2015-57 CCS2015-19
Combinatorial optimization problems cause exponential increases of calculation time in terms of a problem size. In case ... [more] NLP2015-57 CCS2015-19
pp.109-113
NLP 2015-01-26
17:10
Oita Compal Hall The dependence to the active neuron's parameter of the searching performance for TSP's solutions by using DS-net
Hikaru Okuda, Yoshihiro Hayakawa (NIT, Sendai) NLP2014-127
The Inverse function Delayed (ID) model has been proposed as one of the active neuron model. The ID model is expected as... [more] NLP2014-127
pp.83-88
MBE, NC
(Joint)
2014-11-21
11:00
Miyagi Tohoku University A Comparison of Back Propagation Learning between the Inverse-function Delayless Model and a Conventional Model
Yuta Horiuchi (Tohoku Univ), Yoshihiro Hayakawa (SNCT), Takeshi Onomi, Koji Nakajima (Tohoku Univ) NC2014-26
For the combinatorial optimization problem using the hopfield model, avoidance of the local minimum problem is important... [more] NC2014-26
pp.7-10
MBE, NC
(Joint)
2014-11-21
11:25
Miyagi Tohoku University The Relation between Dispersion of Initial Values and Pre-training of Deep Neural Networks
Seitaro Shinagawa (Tohoku univ.), Yoshihiro Hayakawa (SNCT), Takeshi Onomi, Koji Nakajima (Tohoku univ.) NC2014-27
 [more] NC2014-27
pp.11-14
NLP 2014-06-30
16:00
Miyagi Tohoku Univ. Backpropagation learning using inverse function delay-less model
Yuta Horiuchi (Tohoku Univ.), Yoshihiro Hayakawa (SNCT), Takeshi Onomi, Koji Nakajima (Tohoku Univ.) NLP2014-25
The Inverse function Delayed (ID) model has been proposed as one of novel neural models. ID model has a oscillation capa... [more] NLP2014-25
pp.27-30
NLP 2014-06-30
16:25
Miyagi Tohoku Univ. Study on the hardware of the Bidirectional Associative Memories by using the Inverse Function Delayless model
Chunyu Bao, Takeshi Onomi, Yoshihiro Hayakawa, Shigeo Sato, Koji Nakajima (Tohoku Univ.) NLP2014-26
In conventional macro models such as the Hopfield model, the problems that are caused by the solution of the network not... [more] NLP2014-26
pp.31-36
NLP 2014-07-01
10:00
Miyagi Tohoku Univ. Learning Restricted Boltzmann Machine with discrete learning parameter
Seitaro Shinagawa (Tohoku Univ.), Yoshihiro Hayakawa (SNCT), Shigeo Sato, Takeshi Onomi, Koji Nakajima (Tohoku Univ.) NLP2014-27
Recently, the method of Deep Neural Network (DNN) with hierarchical learning has been remarkable for performance to solv... [more] NLP2014-27
pp.37-40
CPM, ED, SDM 2014-05-28
14:00
Aichi   Optimization of the preparation condition of LiMn2O4 film
Yoshihiro Hayakawa, Masaaki Isai, Yasumasa Tomita (Shizuoka Univ.) ED2014-23 CPM2014-6 SDM2014-21
 [more] ED2014-23 CPM2014-6 SDM2014-21
pp.27-32
NLP 2014-01-21
13:30
Hokkaido Niseko Park Hotel DTN routing method by using neural networkas.
Daisuke Sasaki (Tohoku Univ), Yoshihiro Hayakawa (SNCT), Shigeo Sato, Koji Nakajima (Tohoku Univ) NLP2013-136
A Disruption tolerant Network (DTN) is studied as a communicating technique for the time when a network infrastructure w... [more] NLP2013-136
pp.41-44
NLP 2014-01-21
13:50
Hokkaido Niseko Park Hotel Solving Optimization Problems Using DS-net and IDL model
Yuto Watanabe (Tohoku Univ.), Yoshihiro Hayakawa (SNCT), Shigeo Sato, Koji Nakajima (Tohoku Univ.) NLP2013-137
The Inverse function DelayLess (IDL) model has been proposed as one of novel neural models. Since the IDL model can set ... [more] NLP2013-137
pp.45-50
NLP 2014-01-21
15:40
Hokkaido Niseko Park Hotel Neural Network learning using Inverse Function Delayless Model
Yuta Horiuchi (Tohoku Univ.), Yoshihiro Hayakawa (SNCT), Shigeo Sato, Koji Nakajima (Tohoku Univ.) NLP2013-142
The Inverse function Delayed (ID) model has been proposed as one of novel neural models. The ID model has an ability of ... [more] NLP2013-142
pp.73-76
NLP 2014-01-22
10:20
Hokkaido Niseko Park Hotel Studies on the hardware of neural associative memory with a broad basin
Jiang Jing (Tohoku Univ), Yoshihiro Hayakawa (Sendai NT), Shigeo Sato, Koji Nakajima (Tohoku Univ) NLP2013-147
Abstract Because associative operation of the Hopfield neural network model are trapped in spurious memory, the associat... [more] NLP2013-147
pp.99-102
NLP 2013-10-29
13:30
Kagawa Sanport Hall Takamatsu Discussion about the effectiveness of a DS-net and an active neuron model
Yoshihiro Hayakawa, Hikaru Okuda (Sendai NCT.), Yuto Watanabe, Koji Nakajima (Tohoku Univ.) NLP2013-100
The active neuron model, which means an active region in output space,
is an effective tool to avoid local minimum pro... [more]
NLP2013-100
pp.159-164
NLP 2013-10-29
13:45
Kagawa Sanport Hall Takamatsu Fast Calculation of High functional Neural Network by using GPU
Kouta Tanno (Tohoku Univ.), Yoshihiro Hayakawa (Sendai NCT) NLP2013-101
A GPU can compute in highly parallel because it has many cores (processing units). Though it is reported that a high fun... [more] NLP2013-101
pp.165-168
NLP 2012-12-18
09:45
Fukui Fukui City Communication Plaza Inverse Function Delayless (IDL) Model
Yuto Watanabe (Tohoku Univ.), Yoshihiro Hayakawa (SNCT), Shigeo Sato, Koji Nakajima (Tohoku Univ.) NLP2012-98
The Inverse function Delayed (ID) model has been proposed as one of novel neural models. The ID model has the negative r... [more] NLP2012-98
pp.57-60
NLP 2012-12-18
10:10
Fukui Fukui City Communication Plaza Hardware implementation of the discrete Inverse-function Delayed network with Higher order synaptic Connections
Kosuke Matsui (Tohoku Univ.), Yoshihiro Hayakawa (Sendai N.C.T.), Shigeo Sato, Koji Nakajima (Tohoku Univ.) NLP2012-99
The HC-ID network has been proposed as a network model that avoids local minima when it is applied to combinatorial opti... [more] NLP2012-99
pp.61-64
NLP 2012-12-18
10:35
Fukui Fukui City Communication Plaza Optimization of Scheduling in Disruption-Tolerant Networks by Neural Network
Daisuke Sasaki (Tohoku Univ), Yoshihiro Hayakawa (SNCT), Shigeo Sato, Koji Nakajima (Tohoku Univ) NLP2012-100
A Disruption tolerant Network (DTN) is studied as a communicating technique when a network infrastructure was destroyed ... [more] NLP2012-100
pp.65-68
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