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Committee Date Time Place Paper Title / Authors Abstract Paper #
IBISML 2013-03-05
14:35		 Aichi Nagoya Institute of Technology *
Yusuke Kishi, Takuma Nakamura, Tatsuhiro Harada, Takashi Matsumoto (Waseda Univ.) IBISML2012-105		 Infinite Hidden Markov Random Fields have been proposed for image segmentation as a solution to the problem of automatic... [more] IBISML2012-105
pp.87-94
IBISML 2012-11-07
15:30		 Tokyo Bunkyo School Building, Tokyo Campus, Tsukuba Univ. Nested-Hierarchical Dirichlet Process Mixtures for Simultaneous Document-Topic Clustering
Shoji Tominaga, Masamichi Shimosaka, Rui Fukui, Tomomasa Sato (Univ. of Tokyo) IBISML2012-56		 In this paper, we propose a nonparametric Bayesian framework for natural language processing (NLP). Our framework is bas... [more] IBISML2012-56
pp.157-164
SIS, IPSJ-AVM 2012-09-20
12:50		 Osaka Tottori Pref. Osaka Office Huge Flow Detection in Crowded Scenes using Dependent Dirichlet Process HMM
Takuya Okamoto, Katsuya Kondo (Tottori Univ.) SIS2012-20		 In this report, we present the framework of huge flow detection in crowded scenes. The flow analysis is done by using De... [more] SIS2012-20
pp.23-28
IBISML 2010-11-05
15:30		 Tokyo IIS, Univ. of Tokyo [Poster Presentation] Infinite Latent Harmonic Allocation based on Hierarchical Dirichlet Process for Music Signal Analysis
Kazuyoshi Yoshii, Masataka Goto (AIST) IBISML2010-86		 This paper presents a method called the infinite latent harmonic allocation (iLHA) for detecting multiple fundamental fr... [more] IBISML2010-86
pp.195-202
NC, MBE
(Joint)		 2010-03-11
09:25		 Tokyo Tamagawa University Correlated clustering model with hierarchical Dirichlet process
Shunsuke Bamba, Toshiyuki Tanaka (Kyoto Univ.) NC2009-143		 In the case of clustering with a Dirichlet process mixture model, underlying attributes which characterize clusters are ... [more] NC2009-143
pp.327-332
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