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 Conference Papers (Available on Advance Programs)  (Sort by: Date Descending)
 Results 1 - 20 of 25  /  [Next]  
Committee Date Time Place Paper Title / Authors Abstract Paper #
NC, IBISML, IPSJ-BIO, IPSJ-MPS [detail] 2021-06-28
13:00
Online Online Nonparametric Bayesian Deep Visualization
Haruya Ishizuka (Bridgestone Corp.), Daichi Mochihashi (ISM) NC2021-1 IBISML2021-1
(To be available after the conference date) [more] NC2021-1 IBISML2021-1
pp.1-8
SR 2019-01-25
16:40
Fukushima Corasse, Fukushima city (Fukushima prefecture) A study on widely acceptable model for spectrum usage
Kento Yamada, Kenta Umebayashi (TUAT) SR2018-119
We investigate a flexible and scalable spectrum usage model in time domain for an enhanced dynamic spectrum access (DSA)... [more] SR2018-119
pp.141-147
NC, IBISML, IPSJ-BIO, IPSJ-MPS [detail] 2018-06-13
13:00
Okinawa Okinawa Institute of Science and Technology Variable Order Infinite Hidden Markov Models
Kei Uchiumi (Denso ITLab), Daichi Mochihashi (ISM) IBISML2018-5
 [more] IBISML2018-5
pp.31-38
IBISML 2017-11-09
13:00
Tokyo Univ. of Tokyo IBISML2017-35 (To be available after the conference date) [more] IBISML2017-35
pp.1-8
IBISML 2016-11-16
15:00
Kyoto Kyoto Univ. [Poster Presentation]
Kazuyoshi Yoshii, Eita Nakamura, Katsutoshi Itoyama (Kyoto Univ.), Masataka Goto (AIST) IBISML2016-68
(To be available after the conference date) [more] IBISML2016-68
pp.155-162
IBISML 2016-11-17
14:00
Kyoto Kyoto Univ. Infinite graphs with finite diameters
Chihiro Watanabe, Masahiro Nakano, Xiaomeng Wu, Takahito Kawanishi, Kaoru Hiramatsu, Kunio Kashino (NTT) IBISML2016-77
Recently, new stochastic processes have been proposed for analyzing structured data with combinatorial constraints. Part... [more] IBISML2016-77
pp.221-228
SP 2016-10-27
13:00
Shizuoka Shizuoka University. [Invited Talk] Unsupervised Word Discovery based on Bayesian Nonparametrics
Tadahiro Taniguchi (Ritsumeikan) SP2016-44
Word discovery is a critical task in language acquisition for infants.
Human infants can discover words from speech sig... [more]
SP2016-44
pp.21-22
SP 2016-08-24
14:00
Kyoto ACCMS, Kyoto Univ. [Invited Talk] Unsupervised Music Understanding based on Hierarchical Bayesian Acoustic and Language Models
Kazuyoshi Yoshii (Kyoto Univ.) SP2016-29
This paper presents a statistical approach to unsupervised music understanding. Our goal is to estimate musical notes fr... [more] SP2016-29
pp.13-18
EA, SP, SIP 2016-03-29
09:00
Oita Beppu International Convention Center B-ConPlaza [Poster Presentation] Sparse Kernel Regression Based on Nonparametric Bayesian Model
Atsushi Kojima, Suguru Yasutomi, Toshihisa Tanaka (TUAT) EA2015-126 SIP2015-175 SP2015-154
In general, one of major challenges in regression analysis is how to select an appropriate model. As the number of obser... [more] EA2015-126 SIP2015-175 SP2015-154
pp.335-340
IBISML 2015-11-27
14:00
Ibaraki Epochal Tsukuba [Poster Presentation] Stochastic process representation of R-tree
Masahiro Nakano, Xiaomeng Wu, Minoru Mori, Akisato Kimura, Kunio Kashino (NTT) IBISML2015-76
This paper discusses a new stochastic process that represents the in nitely exchangeable rectangular partitioning of a m... [more] IBISML2015-76
pp.175-182
IBISML 2014-11-18
15:00
Aichi Nagoya Univ. [Poster Presentation] An Infinite Superimposed Discrete All-pole Model based on Gamma Processes for Music Signal Analysis
Kazuyoshi Yoshii, Katsutoshi Itoyama (Kyoto Univ.), Masataka Goto (AIST) IBISML2014-60
This paper presents a probabilistic model that is used for decomposing music audio signals into the three elements of so... [more] IBISML2014-60
pp.191-198
SP, IPSJ-MUS 2014-05-24
10:30
Tokyo   [Invited Talk] Infinite data analysis and Bayesian nonparametrics for audio signal processing
Masahiro Nakano (NTT) SP2014-3
Bayesian nonparametrics has been an active area of research. Althoug we can construct a variety of models based on famou... [more] SP2014-3
pp.13-18
IBISML 2013-11-13
15:45
Tokyo Tokyo Institute of Technology, Kuramae-Kaikan [Poster Presentation] Infinite Positive Semidefinite Tensor Factorization based on Gamma Process for Music Signal Analysis
Kazuyoshi Yoshii (AIST), Ryota Tomioka (Univ. of Tokyo), Daichi Mochihashi (ISM), Masataka Goto (AIST) IBISML2013-57
This paper presents positive semidefinite tensor factorization (PSDTF) that is a natural extension of nonnegative matrix... [more] IBISML2013-57
pp.161-168
IBISML 2013-11-13
15:45
Tokyo Tokyo Institute of Technology, Kuramae-Kaikan [Poster Presentation] Floor-plan partitioning stochastic processes for relational data analysis
Masahiro Nakano, Katsuhiko Ishiguro, Akisato Kimura, Takeshi Yamada, Naonori Ueda (NTT) IBISML2013-62
This paper presents a floor-plan partitioning stochastic process, that can potentially generate arbitrary rectangular pa... [more] IBISML2013-62
pp.197-204
SIP, CAS, CS 2013-03-15
15:35
Yamagata Keio Univ. Tsuruoka Campus (Yamagata) Towards driving behavior prediction: Applying nonparametric Bayesian approach to driving operation time series data
Ryunosuke Hamada, Takatomi Kubo, Kazushi Ikeda, Zujie Zhang, Tomohiro Shibata (NAIST), Takashi Bando, Masumi Egawa (DENSO) CAS2012-142 SIP2012-173 CS2012-148
Prediction of driving behaviors is important problem in developing a next-generation driving support system. In order to... [more] CAS2012-142 SIP2012-173 CS2012-148
pp.265-270
IBISML 2012-11-07
15:30
Tokyo Bunkyo School Building, Tokyo Campus, Tsukuba Univ. Subset Infinite Relational Model
Katsuhiko Ishiguro, Naonori Ueda, Hiroshi Sawada (NTT) IBISML2012-37
We propose a new probabilistic generative model for analyzing sparse and noisy relational data, such as friend-links on ... [more] IBISML2012-37
pp.23-30
IBISML 2012-11-07
15:30
Tokyo Bunkyo School Building, Tokyo Campus, Tsukuba Univ. Infinite Composite Autoregressive Models based on Gamma Processes for Music Signal Analysis
Kazuyoshi Yoshii, Masataka Goto (AIST) IBISML2012-51
This paper presents novel statistical models that can be used for multiple fundamental frequency (F0) estimation and tim... [more] IBISML2012-51
pp.121-128
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
PRMU, IBISML, IPSJ-CVIM
(Joint) [detail]
2012-09-03
10:30
Tokyo   Nonparametric Bayesian Estimation for Automatic Image Annotation Using Gaussian Mixture Model
Yukihiro Tsuboshita, Noriji Kato (Fuji Xerox), Masato Okada (The universisty of Tokyo) PRMU2012-40 IBISML2012-23
Automatic image annotation (AIA) is a process to automatically assign metadata to a digital image in the form of caption... [more] PRMU2012-40 IBISML2012-23
pp.93-98
PRMU, NLC 2012-06-29
17:00
Tokyo   Bayesian Nonparametric Approach to Audio Event Detection
Yasunori Ohishi (NTT), Daichi Mochihashi, Tomoko Matsui (ISM), Masahiro Nakano, Hirokazu Kameoka, Tomonori Izumitani, Kunio Kashino (NTT) NLC2012-9 PRMU2012-29
As the amount of available multimedia data increases, the technique to automatically extract the significant information... [more] NLC2012-9 PRMU2012-29
pp.37-42
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