Committee |
Date Time |
Place |
Paper Title / Authors |
Abstract |
Paper # |
NC, NLP (Joint) |
2016-01-29 12:10 |
Fukuoka |
Kyushu Institute of Technology |
Accelerated quasi-Newton Training using Nesterov's Gradient Method Hiroshi Ninomiya (SIT) NLP2015-141 |
This paper describes a new quasi-Newton based accelerated technique for training of neural networks. Recently, Nesterov’... [more] |
NLP2015-141 pp.87-92 |
NC, NLP (Joint) |
2016-01-29 13:35 |
Fukuoka |
Kyushu Institute of Technology |
Analysis of periodic orbits in dynamic binary neural networks Kazuma Makita, Ryuji Sato, Toshimichi Saito (HU) NC2015-61 |
This paper considers analysis of dynamic binary neural networks.
The networks can generate various binary periodic orb... [more] |
NC2015-61 pp.25-28 |
NC, NLP (Joint) |
2016-01-29 14:00 |
Fukuoka |
Kyushu Institute of Technology |
Analysis of spurious memories in hysteresis associative memories Takahiro Ishikawa, Kei Yamaoka, Toshimichi Saito (HU) NC2015-62 |
The hysteresis neural network is a continuous-time network characterized by binary hysteresis activation function.
Th... [more] |
NC2015-62 pp.29-32 |
NC, NLP (Joint) |
2016-01-29 14:25 |
Fukuoka |
Kyushu Institute of Technology |
Ego-motion estimation system for a small UAV inspired by the motion-detection model of the insect's visual system Shota Tsunekawa, Fuyuki Ueno (Osaka Univ.), Kazuo Ishii (Kyushu I.T.), Tetsuya Yagi, Hirotsugu Okuno (Osaka Univ.) NC2015-63 |
In this study, we devised an algorithm that estimates the 6 degree-of-freedom ego-motion of a small unmanned aerial vehi... [more] |
NC2015-63 pp.33-38 |
NC, NLP (Joint) |
2016-01-29 14:50 |
Fukuoka |
Kyushu Institute of Technology |
The dynamics of the neuronal cells and an astrocyte during the generation of the carbachol-induced beta oscillation in rat hippocampal slices. Itsuki Kageyama, Katsumi Tateno, Kiyohisa Natsume (KIT) NC2015-64 |
Carbachol,a cholinergic agent induces bursts of beta oscillations occur in rat hippocampal slices. The duration of the b... [more] |
NC2015-64 pp.39-44 |
NC, NLP (Joint) |
2016-01-29 15:25 |
Fukuoka |
Kyushu Institute of Technology |
Statistical Mechanics of Perceptron Learning with Noisy Teacher Arata Honda, Kazushi Ikeda (NAIST) NC2015-65 |
Learning curves of simple perceptron were derived here. They have been analyzed for half a century and the learning curv... [more] |
NC2015-65 pp.45-48 |
NC, NLP (Joint) |
2016-01-29 15:50 |
Fukuoka |
Kyushu Institute of Technology |
Node-perturbation Learning for Soft-committee machine Kazuyuki Hara (Nihon Univ.), Kentaro Katahira (Nagoya Univ.) NC2015-66 |
Node perturbation learning is a stochastic gradient descent method for neural networks. It estimates the gradient of the... [more] |
NC2015-66 pp.49-54 |
NC, NLP (Joint) |
2016-01-29 16:15 |
Fukuoka |
Kyushu Institute of Technology |
Proposal of novel dropout method and its analysis of dynamic property Daisuke Saitoh, Tasuku Kondo, Kazuyuki Hara (Nihon Univ.) NC2015-67 |
Deep learning that use a large network and includes many units tends to occur the overfitting. Therefore, to avoid the o... [more] |
NC2015-67 pp.55-60 |
NC, NLP (Joint) |
2016-01-29 16:40 |
Fukuoka |
Kyushu Institute of Technology |
Simultaneous visualization of topics and human relations from e-mail dataset by Tensor SOM. Hajime Hatano, Tetsuo Furukawa (KyuTech) NC2015-68 |
[more] |
NC2015-68 pp.61-66 |