Thu, Jan 26 AM
09:00 - 12:10 |
| (1) |
09:00-09:25 |
Storage capacity of the associative memory model with the zero-order synaptic decay |
Ryota Miyata (Tokyo Tech.), Jun Tsuzurugi (Okayama Univ. Sci.), Toru Aonishi (Tokyo Tech.), Koji Kurata (Univ. Ryukyu.) |
| (2) |
09:25-09:50 |
Influence on the Storage Capacity by the Difference Between Network Structure and a Pattern Set |
Masaya Nakakura, Keisuke Terayama, Yukari Yamauchi (NU) |
| (3) |
09:50-10:15 |
Study on Sequential Associative Memory in Chaos Neural Network |
Yoshiaki Sato, Yukari Yamauchi (Nihon Univ.) |
| (4) |
10:15-10:40 |
Statistic and dynamics of the Hopfield model with unlearning term |
Haruka Otani, Midori Yoshida, Tatsuya Uezu (Nara Woman's Univ.) |
| |
10:40-10:55 |
Break ( 15 min. ) |
| (5) |
10:55-11:20 |
Bifurcation of Simple Pulse-Coupled Spiking Neurons for Shape of Base Signals |
Shota Kirikawa, Takashi Ogawa, Toshimichi Saito (HU) |
| (6) |
11:20-11:45 |
Analysis of Self-Organizing Digital Spike Phase Maps |
Narutoshi Horimoto, Takashi Ogawa, Toshimichi Saito (HU) |
| (7) |
11:45-12:10 |
Comparison and Evaluation of Growing Complex Network Generated by Similarities |
Keisuke Terayama, Yukari Yamauchi (NU) |
| |
12:10-13:10 |
Lunch Break ( 60 min. ) |
Thu, Jan 26 PM
13:10 - 16:05 |
| (8) |
13:10-14:10 |
[Invited Talk]
Grand Challenge in Artificial Intelligence |
Hitoshi Matsubara (FUN) |
| |
14:10-14:25 |
Break ( 15 min. ) |
| (9) |
14:25-14:50 |
A recurrent network for multisensory integration
-- Identification of common sources of audiovisual stimuli -- |
Itsuki Yamashita (Tokyo Univ.), Kentaro Katahira (JST), Yasuhiko Igarashi (Tokyo Univ.), Kazuo Okanoya (JST), Masato Okada (Tokyo Univ.) |
| (10) |
14:50-15:15 |
Cluster analysis and Gaussian mixture estimation of correlated time-series by means of multi-dimensional scaling |
Takero Ibuki (Hokkaido Univ.), Sei Suzuki (Aoyama-Gakuin Univ.), Jun-ichi Inoue (Hokkaido Univ.) |
| (11) |
15:15-15:40 |
The learning theory and algorithm of latent multi-dynamical systems
-- Implementation by higher-order topographic mapping -- |
Tetsuo Furukawa, Takashi Ohkubo (Kyutech) |
| (12) |
15:40-16:05 |
Critical phenomena in mean-field Ising models and time-series prediction |
Shunsuke Higano, Jun-ichi Inoue (Hokkaido Univ.) |
Fri, Jan 27 AM
09:30 - 16:15 |
| (13) |
09:30-09:55 |
A statistical analysis of soft-margin support vector machines for non-separable problems |
Hiroyuki Funaya, Kazushi Ikeda (NAIST) |
| (14) |
09:55-10:20 |
A Study on Approximate Probabilistic Reasoning Algorithm for assuring and correcting accuracy results on Bayesian Networks |
Shuhei Wakasaki, Daisuke Kitakoshi, Masato Suzuki (TNCT) |
| (15) |
10:20-10:45 |
On the Relationship between Learning Coefficient for Bayesian Estimation and Average of Acceptance Rate for Metropolis Algorithm |
Kenji Nagata (The Univ. of Tokyo), Masato Okada (Univ. of Tokyo/RIKEN) |
| |
10:45-11:00 |
Lunch Break ( 15 min. ) |
| (16) |
11:00-11:25 |
Analysis of evoked potentials to auditory pair stimuli for estimation of uncomfortable loudness level |
Kohei Fujii (NAIST), Shinobu Adachi, Koji Morikawa (Panasonic), Kazushi Ikeda (NAIST) |
| (17) |
11:25-11:50 |
Decoding performance of quantum fluctuation for Sourlas code |
Yosuke Otsubo (Univ. of Tokyo), Jun-ichi Inoue (Hokkaido Univ.), Kenji Nagata (Univ. of Tokyo), Masato Okada (Univ. of Tokyo/RIKEN) |
| (18) |
11:50-12:15 |
Tensor decomposition based on self-organizing map |
Toru Iwasaki, Saori Wada, Tetsuo Furukawa (KIT) |
| |
12:15-13:30 |
Break ( 75 min. ) |
| (19) |
13:30-13:55 |
Analysis of Time Series Data Accompanied with Rewards and Actions using Reinforcement Learning |
Hideki Asoh, Masanori Shiro, Toshihiro Kamishima, Shotaro Akaho (AIST), Takahide Kohro (Univ. Tokyo) |
| (20) |
13:55-14:20 |
A Method to Improve Efficiency of Reinforcement Learning by Using a Vector Representation of a Policy |
Daiki Ando, Daisuke Kitakoshi, Masato Suzuki (TNCT) |
| (21) |
14:20-14:45 |
Rotations of Preferred Directions Facilitate Recovery Process in Damaged Motor Cortex |
Ken Takiyama (Univ. of Tokyo), Masato Okada (Univ. of Tokyo/RIKEN) |
| |
14:45-15:00 |
Break ( 15 min. ) |
| (22) |
15:00-15:25 |
The M-best Discrete Optimization Method for Sparsely Connected Multi-body Model |
Masashi Kato, Masato Inoue (Waseda Univ.) |
| (23) |
15:25-15:50 |
Higher order correlation in a feedforward network with Mexican-hat-type connectivity |
Yasuhiko Igarashi, Masato Okada (Tokyo Univ.) |
| (24) |
15:50-16:15 |
Neural Network Model with Sparse and Local Excitation |
Akira Manda (Univ of Tokyo), Toshiaki Omori (Univ of Tokyo/RIKEN), Jun Kitazono (Univ of Tokyo/JSPS), Masato Okada (Univ of Tokyo/RIKEN) |