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Technical Committee on Neurocomputing (NC) (Searched in: 2008)
Search Results: Keywords 'from:2009-01-19 to:2009-01-19'
| Committee | Date Time | Place | Paper Title / Authors | Abstract | Paper # | |
| NC | 2009-01-19 10:30 |
Hokkaido | Hokkaido Univ. | Solving Relay Dedicated Node Assignment Problem in Wireless Sensor Networks Using PSO with Suppression Masaki Yoshimura, Hidehiro Nakano, Arata Miyauchi (Musashi Inst. of Tech.)  NC2008-82 |
In sensor networks, learge number of sensor nodes are scattered in an observed target field. Each sensor node transmit... [more] |
NC2008-82 pp.1-6 |
| NC | 2009-01-19 10:55 |
Hokkaido | Hokkaido Univ. | Reinforcement Learning Using Selective Desensitization Neural Networks in the State Space with Redundant dimensions Tomoyuki Shimbo, Ken Yamane, Masahiko Morita (Univ. of Tsukuba) NC2008-83 |
Reinforcement learning has a problem that it requires a long time particularly when the state space is high dimensional ... [more] | NC2008-83 pp.7-12 |
| NC | 2009-01-19 11:20 |
Hokkaido | Hokkaido Univ. | Handwritten Character Recognition by NGxSOM Kouichi Gunya, Makoto Otani, Tetsuo Furukawa (Kyushu Inst. of Tech.) NC2008-84 |
We have proposed SOM$^2$ and NG$\times$SOM algorithms. These algorithms have the ability of representing a set of data d... [more] | NC2008-84 pp.13-18 |
| NC | 2009-01-19 11:45 |
Hokkaido | Hokkaido Univ. | A probabilistic model of maximum margin matrix factorization with ARD prior Masahiro Furuya (Nara Inst. of Scie and Tech), Shigeyuki Oba (Kyoto Univ.), Shin Ishii (Nara Inst.of Scie and Tech/Kyoto Univ.) NC2008-85 |
Various methods for missing value estimation of matrix data have been proposed based on low-rank approximation of matrix... [more] | NC2008-85 pp.19-24 |
| NC | 2009-01-19 13:30 |
Hokkaido | Hokkaido Univ. | Structure estimation using time-dependent data in hidden Markov models Masashi Matsumoto, Sumio Watanabe (Tokyo Inst. of Tech.) NC2008-86 |
A lot of learning machines used in information science, for example, mixture models, artificial neural networks, Bayesia... [more] | NC2008-86 pp.25-30 |
| NC | 2009-01-19 13:55 |
Hokkaido | Hokkaido Univ. | On the Effect of Hyperparameter to Generalization Error in Variational Bayes Learning Shinji Oyama, Sumio Watanabe (Tokyo Inst. of Tech.) NC2008-87 |
In variational Bayes learning, the probability distribution of the hidden variable and parameter is made by the mean fie... [more] | NC2008-87 pp.31-36 |
| NC | 2009-01-19 14:20 |
Hokkaido | Hokkaido Univ. | Experimental Study of Bayesian Learning using Langevin Equation in Singular Learing Machines Taruhi Iwagaki, Sumio Watanabe (Tokyo Inst. of Tech.) NC2008-88 |
Langevin equation implies an algorithm that could make samples from the stationary distribution of a biased random walk ... [more] | NC2008-88 pp.37-42 |
| NC | 2009-01-19 14:45 |
Hokkaido | Hokkaido Univ. | Node perturbation learning with noisy reference Tatsuya Cho (Univ. of Tokyo), Kentaro Katahira, Masato Okada (Univ of Tokyo/RIKEN Brain Scie Inst.) NC2008-89 |
We propose a node perturbation learning with noisy reference signal. Recently, the method for node perturbation has inv... [more] |
NC2008-89 pp.43-47 |
| NC | 2009-01-19 15:10 |
Hokkaido | Hokkaido Univ. | Statistical mechanics of the Hopfield model with replacing units Yasunao Komatsu, Toru Aonishi (Tokyo Inst. of Tech.), Koji Kurata (Univ. of Ryukyus) NC2008-90 |
There is a critical memory capacity in the Hopfield model. If the number of embed patterns surpasses the crirical number... [more] | NC2008-90 pp.49-54 |
| NC | 2009-01-19 15:45 |
Hokkaido | Hokkaido Univ. | Prior Knowledge-Based Stepwise Structure Learning of Bayesian Networks Hirotaka Fukui (Nagoya Inst. of Tech.), Daisuke Kitakoshi (Tokyo National College of Tech.) NC2008-91 |
Bayesian networks are graphical models representing stochastic dependencies among random variables and are applied to a ... [more] | NC2008-91 pp.55-60 |
| NC | 2009-01-19 16:10 |
Hokkaido | Hokkaido Univ. | The relativity of time to filling-in to eye movement Masae Yokota (Nagoya Bunri Univ.), Yasunari Yokota (Gifu Univ.) NC2008-92 |
When a small area (filling-in target) that has a different texture from its surroundings is presented to a subject’s per... [more] | NC2008-92 pp.61-66 |
| NC | 2009-01-19 16:35 |
Hokkaido | Hokkaido Univ. | Progress Curve Analysis of Multisite Phosphorylation Using Michaelis-Menten Equations Yumi Nakagawa (Kyushu Inst. of Tech.), Hideyuki Cateau (Kyushu Inst. of Tech/RIKEN) NC2008-93 |
Cooperativity in multisite phosphorylation that is an enhancement or a suppression of phosphorylation at some site due t... [more] | NC2008-93 pp.67-71 |
| NC | 2009-01-19 17:00 |
Hokkaido | Hokkaido Univ. | The significance of a nonlinear transformation and a role of local neurons in the Drosophila primary olfactory center Ryota Satoh (Univ. of Tokyo.), Masafumi Oizumi (Univ. of Tokyo/Research Fellw of the Japan), Hokto Kazama (Harvard Medical School), Masato Okada (Univ. of Tokyo/Research Fellw of the Japan) NC2008-94 |
Recent investigations have shown that, in the Drosophila olfactory system, olfactory receptor neurons (ORNs) are compara... [more] | NC2008-94 pp.73-78 |
| NC | 2009-01-19 17:25 |
Hokkaido | Hokkaido Univ. | Reinforcement Meta-learning rule solves the distal reword problem Shojiro Araki (Tamagawa Univ), Yutaka Sakai (Tamagawa Univ. Brain Scie Inst.) NC2008-95 |
It is known that spike-timing-dependent synaptic plasticity (STDP) epends on the initial strength of the synapse, and th... [more] | NC2008-95 pp.79-83 |
| NC | 2009-01-20 10:00 |
Hokkaido | Hokkaido Univ. | [Invited Talk]
Chaotic itinerancy in the hippocampal CA3 and contractive affine transformations in CA1 provide a dynamical interpretation of complex memory Ichiro Tsuda (Hokkaido Univ.) NC2008-96 |
Since David Marr's pioneering paper entitled “Simple memory: A model for the archecortex” published in 1969, the functio... [more] | NC2008-96 pp.85-86 |
| NC | 2009-01-20 13:00 |
Hokkaido | Hokkaido Univ. | [Invited Talk]
Cross-modal and scale-free action representation in sensorimotor maps Alex Pitti (ERATO/JST) NC2008-97 |
Biological systems constantly engage themselves in sensorimotor processes binding dynamically neural regions to form coh... [more] | NC2008-97 p.87 |
| NC | 2009-01-20 14:40 |
Hokkaido | Hokkaido Univ. | Which model can properly describe dynamics and smoothness of firing rate? Ken Takiyama (The Univ. of Tokyo), Kentaro Katahira, Masato Okada (The Univ. of Tokyo/RIKEN) NC2008-98 |
We construct the algorithm using belief propagation(BP), which algorithm simultaneously estimates firing rate and calcu... [more] |
NC2008-98 pp.89-94 |
| NC | 2009-01-20 15:05 |
Hokkaido | Hokkaido Univ. | A Neural Network Model Explaining the Motion Detection Sensitivity Enhanced and Degraded by Induced Motion Satohiro Tajima, Hiromasa Takemura, Ikuya Murakami (Univ. Tokyo), Masato Okada (Univ. Tokyo/RIKEN) NC2008-99 |
Motion in the visual context is known to cause a repulsive bias in the perception of the target motion. This phenomenon ... [more] | NC2008-99 pp.95-100 |
| NC | 2009-01-20 15:30 |
Hokkaido | Hokkaido Univ. | Model Adaptation in Preference Modeling Hideki Asoh, Yoichi Motomura (National Inst. of Adv Ind Scie and Tech.), Chihiro Ono (KDDI R&D Lab,Inc.) NC2008-100 |
Modeling users' preference becomes important for providing personalized services. In order to construct context-aware st... [more] | NC2008-100 pp.101-106 |
| NC | 2009-01-20 15:55 |
Hokkaido | Hokkaido Univ. | Research on Human Behavior in Learning Tasks and a Proposal for a Change Detection Method Shohei Shimada, Kyosuke Nishida (Hokaido Univ.), Satoru Ishikawa (Hokusei Gakuen Univ.), Koichiro Yamauchi (Hokaido Univ.) NC2008-101 |
Online learning classifiers need to detect and respond quickly to concept changes in the case where the target concept... [more] |
NC2008-101 pp.107-112 |
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