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All Technical Committee Conferences (Searched in: All Years)
| Committee | Date Time | Place | Paper Title / Authors | Abstract | Paper # | |
| USN, IPSJ-UBI | 2009-07-16 14:30 |
Kyoto | ATR (Kyoto) | Applying a Probabilistic Inference Stream Processing Engine to a Camera Sensor Network Ryo Sato, Hideyuki Kawashima, Hiroyuki Kitagawa (Univ. of Tsukuba)  USN2009-20 |
The purpose of this paper is to appropriately incorporate Bayesian networks into a relational stream processing system ... [more] |
USN2009-20 pp.69-74 |
| NC, MBE (Joint) |
2009-03-12 13:50 |
Tokyo | Tamagawa Univ. | Model Learning of Normalized Gaussian Networks Using On-line Information Bottleneck EM Algorithm Satoshi Imai, Hiroyuki Seki (Nara Inst. of Sci and Tech.) NC2008-143 |
In this report, we propose a new learning method of stochastic models which have hidden variables. This method estimate... [more] |
NC2008-143 pp.237-242 |
| NC, MBE (Joint) |
2009-03-13 13:25 |
Tokyo | Tamagawa Univ. | Infant's Indoor Behavior Recognition using Bayesian Inference in combination with Tree Augumented Naive Bayes and Baysian Network Shouzou Ishikawa (Tokyo Metropolitan Coll. of Ind Tech.), Yoichi Motomura, Yoshifumi Nishida (Digital Human Resarch Center,National Inst. of Adv Ind and Tech.), Kazuyuki Hara (Tokyo Metropolitan Coll. of Ind Tech.) NC2008-156 |
The purpose of this study is to prevent injury in children. It is important to recognize and observe infant's behavior ... [more] |
NC2008-156 pp.313-318 |
| NC, MBE (Joint) |
2009-03-13 13:50 |
Tokyo | Tamagawa Univ. | Consumer Behavior Modeling Based on Large Scale Data and Cognitive Structures Tsukasa Ishigaki, Yoichi Motomura, Hei Chan (National Inst. of Adv Ind Sci and tech.) NC2008-157 |
Large scale data of human behavior records in daily life or shopping such as POS data can be observed by a development o... [more] | NC2008-157 pp.319-324 |
| 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 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, MBE (Joint) |
2008-12-20 10:00 |
Aichi | Nagoya Inst. Tech. | Clustering complex networks with the prior based on degree distribution Naoyuki Harada, Ichiro Takeuchi (NIT), Ryohei Nakano (Chubu Univ.) NC2008-73 |
Newman et al. proposed a graph clustering method based on a robabilistic mixture model with only the general assumption ... [more] | NC2008-73 pp.1-6 |
| PRMU | 2008-12-19 09:30 |
Kumamoto | Kumamoto Univ. | Image Matching using Bayesian Networks Constructed out of Local Color Features Nao Matsumura, Hajimu Kawakami (Ryukoku Univ) PRMU2008-169 |
Image matching method based on distribution of pixel values has been proposed. We propose extending the distribution ... [more] |
PRMU2008-169 pp.129-134 |
| SP, NLC | 2008-12-09 11:15 |
Tokyo | Waseda Univ. | Music suppression method for single channel speech mixed with BGM using Bayesian networks Hiroaki Itou, Takanori Nishino, Norihide Kitaoka, Kazuya Takeda (Nagoya Univ.) NLC2008-27 SP2008-82 |
A non-parametric stochastic method of the single-channel speech extraction from a mixture of speech and music is propose... [more] | NLC2008-27 SP2008-82 pp.19-24 |
| NC, MBE (Joint) |
2008-03-12 10:00 |
Tokyo | Tamagawa Univ | Gaussian Graphical Model on Scale-Free Network Takafumi Usui, Muneki Yasuda, Kazuyuki Tanaka (Tohoku Univ.) NC2007-112 |
We consider probabilistic inferences formulated by using Gaussian graphical models on scale free networks. We can deriv... [more] |
NC2007-112 pp.1-5 |
| NC, MBE (Joint) |
2008-03-13 15:20 |
Tokyo | Tamagawa Univ | Learning and Inference of Probabilistic Causal Structure Model for Indoor Behavior Prediction of Infants Satoshi Kawata (Tohoku Univ.), Yoichi Motomura, Yoshifumi Nishida (AIST), Shouzou Ishikawa (Metropolitan College of Industrial Technology), Kazuyuki Tanaka (Tohoku Univ.) NC2007-159 |
In order to contribute to saving children exposed to daily dangers, monitoring children's everyday behavior is essenti... [more] |
NC2007-159 pp.279-282 |
| DE | 2007-07-03 13:35 |
Miyagi | Akiu hot springs (Sendai) | The Design of a Probabilistic Inference Sensor Database System Hideyuki Kawashima, Hiroyuki Kitagawa (Univ. of Tsukuba) DE2007-80 |
Applications of ubiquitous sensor networks are widely spread to natural environment monitoring, civil environment monito... [more] | DE2007-80 pp.351-356 |
| NC | 2007-06-15 13:25 |
Okinawa | OIST Seaside House | Learning of Neural Networks with Dichotomic Random Teacher Signals Yoshifusa Ito (AGU), Cidambi Srinivasan (UKY), Hiroyuki Izumi (AGU) NC2007-21 |
Learning with dichotomic random teacher signals is a hard task for neural networks, because the learning cannot be compl... [more] | NC2007-21 pp.75-80 |
| NC | 2007-03-14 09:30 |
Tokyo | Tamagawa University | On the Two Kullback Divergences in Approximating Bayesian Posterior Distributions Kazuho Watanabe, Sumio Watanabe (Tokyo Inst. of Tech.) |
Some methods have been proposed and used for approximating Bayesian learning.Although they have provided efficient learn... [more] | NC2006-134 pp.97-102 |
| ET | 2007-03-09 15:45 |
Kochi | Estimation of Learner's Property Using Bayesian networks in e-Learning System Takashi Sumada, Tetsuya Matsumoto, Noboru Ohnishi (Nagoya Univ) |
In this paper, we propose a method to construct learner model using Bayesian network which is suitable for modeling comp... [more] | ET2006-141 pp.203-208 |
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| NC | 2006-03-15 11:25 |
Tokyo | Tamagawa University | Exchange Monte Carlo Method for Bayesian Learning of Singular Learning Machines Kenji Nagata, Sumio Watanabe (Tokyo Inst. of Tech.) |
A lot of singular learning machines such as neural networks, normal mixtures, Bayesian networks and hidden Markov models... [more] | NC2005-118 pp.73-78 |
| KBSE, JSAI-KBS | 2006-01-23 14:10 |
Kanagawa | Keio Univ.(Hiyoshi) | Approach for Injury surveillance system to prevent child accident
-- Aquiring probabilistic knowledge and reuse -- Yoichi Motomura, Yoshifumi Nishida (AIST), Tatushiro Yamanaka (RCC), , , , Hiroshi Mizoguchi (Tokyo Univ. of Science) |
We introduce our research project for preventing children’s accidents. Injury surveillance systems, probabilistic modeli... [more] | KBSE2005-23 pp.13-18 |
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