Search Results 1-20 of 38

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  • Momentum-Space Renormalization Group Transformation in Bayesian Image Modeling by Gaussian Graphical Model

    Tanaka Kazuyuki , Nakamura Masamichi , Kataoka Shun , Ohzeki Masayuki , Yasuda Muneki

    Journal of the Physical Society of Japan 87(8), 085001-085001, 2018-08-15

    DOI 

  • Traffic State Interpolation of Unobserved Road Links by Accumulated Data Using the Relationships of Links in Road Network  [in Japanese]

    Hara Yusuke , HANAOKA Yohei , KUWAHARA Masao

    … To solve the problem, we model the traffic states in road network by Gaussian Graphical Model (GGM) and interpolate the road link speed. … We propose two approaches, one is structural GGM and another is the estimation by Graphical Lasso and we extend these methods for partial observation by EM algorithm. …

    JSTE Journal of Traffic Engineering 2(1), 1-10, 2016

    J-STAGE 

  • ESTIMATING SCALE-FREE NETWORKS VIA THE EXPONENTIATION OF MINIMAX CONCAVE PENALTY

    Hirose Kei , Ogura Yukihiro , Shimodaira Hidetoshi

    … <p>We consider the problem of sparse estimation of undirected graphical models via the <i>L</i>1 regularization. …

    Journal of the Japanese Society of Computational Statistics 28(1), 139-154, 2015

    J-STAGE 

  • Finding scale-free networks of Gaussian graphical models by sampling  [in Japanese]

    SHIKITA Shota , MARUYAMA Osamu

    … The problem of learning the structure of a Gaussian graphical model is to infer the graph representing the relationship between random variables of the model from sample. …

    電子情報通信学会技術研究報告 = IEICE technical report : 信学技報 113(476), 15-22, 2014-03-06

  • INTRODUCTION TO NESTED MARKOV MODELS

    Shpitser Ilya , J. Evans Robin , S. Richardson Thomas , M. Robins James

    Graphical models provide a principled way to take advantage of independence constraints for probabilistic and causal modeling, while giving an intuitive graphical description of "qualitative features" useful for these tasks. … A popular graphical model, known as a Bayesian network, represents joint distributions by means of a directed acyclic graph (DAG). …

    Behaviormetrika 41(1), 3-39, 2014

    J-STAGE 

  • Comparison of sparse non-directional graphical models on anatomical landmark distances by the Smoothly Clipped Absolute Deviation (SCAD) and the Graphical Lasso  [in Japanese]

    Hanaoka Shouhei , Masutani Yoshitaka , Nemoto Mitsutaka , Nomura Yukihiro , Miki Soichiro , Yoshikawa Takeharu , Hayashi Naoto , Ohtomo Kuni

    … The system utilizes a multivariable Gaussian statistical model on inter-landmark distances which were estimated with Tikhonov or L1-norm regularization terms. …

    IEICE technical report. 113(146), 7-12, 2013-07-18

  • Estimation of Large-scale Graphical Models for Data Assimilation  [in Japanese]

    上野 玄太

    統計数理 61(1), 17-46, 2013-06

  • Construction of a sparse non-directional graphical model on anatomical landmark distances by the Graphical Lasso : Feasibility study for application to automatic landmark detection system  [in Japanese]

    Hanaoka Shouhei , Masutam Yoshitaka , Nemoto Mitsutaka , Nomura Yukihiro , Miki Soichiro , Yoshikawa Takeharu , Hayashi Naoto , Ohtomo Kuni

    … The system utilizes a non-sparse multivariable Gaussian statistical model on inter-landmark distances. … The aim of this study is to extend our previous method to sparse multivariable Gaussian model by GPGPU-implemented Graphical lasso method. … The probabilistic distribution of inter-landmark distances was estimated as a multiple Gaussian distribution with a sparse precision matrix. …

    IEICE technical report. 112(411), 13-18, 2013-01-24

  • Design of probabilistic image inpainting filters using Gaussian graphial models  [in Japanese]

    KITAGAWA Tomotaka , YASUDA Muneki , TANAKA Kazuyuki

    … Pixel-based probabilistic image inpainting filters on the basis of a Gaussian graphical models (Gaussian Markov random fields), which can fast reconstruct damaged parts of images, have been proposed by some authors. …

    IEICE technical report. Neurocomputing 112(298), 57-62, 2012-11-09

    References (10)

  • Structure Learning for Anomaly Localization  [in Japanese]

    HARA Satoshi , WASHIO Takashi

    … In this paper, we propose a graphical model learning algorithm for an anomaly localization. …

    電子情報通信学会技術研究報告. IBISML, 情報論的学習理論と機械学習 = IEICE technical report. IBISML, Information-based induction sciences and machine learning 112(279), 17-22, 2012-10-31

    References (15)

  • LOCAL VARIATIONAL MESSAGE PROPAGATION FOR GAUSSIAN GRAPHICAL MODEL

    CHEN YARUI , XIE HAILIN

    ICIC express letters. Part B, Applications : an international journal of research and surveys 3(5), 1303-1310, 2012-10

  • Gaussian FoE model with correlations among color components  [in Japanese]

    MURAYAMA Ryuta , YASUDA Muneki , WAIZUMI Yuji , TANAKA Kazuyuki

    … In this paper we design a new prior probability for color images, which can take correlations among color components into account, by extending a fields of experts model with a Gaussian distribution, called Gaussian fields of experts (GFoE), and by using machine learning techniques. … We show that our proposed model gives better results than a GFoE which does not take correlations among color components into account with the same order of computational cost. …

    電子情報通信学会技術研究報告 : 信学技報 111(275), 105-111, 2011-11-09

  • Learning a Graphical Structure with Clusters  [in Japanese]

    HARA Satoshi , WASHIO Takashi

    … In this paper, we propose an estimation technique of a graphical model with some unknown clusters. …

    電子情報通信学会技術研究報告 : 信学技報 111(275), 19-24, 2011-11-09

  • Gaussian FoE model with correlations among color components  [in Japanese]

    MURAYAMA Ryuta , YASUDA Muneki , WAIZUMI Yuji , TANAKA Kazuyuki

    電子情報通信学会技術研究報告. IBISML, 情報論的学習理論と機械学習 = IEICE technical report. IBISML, Information-based induction sciences and machine learning 111(275), 105-111, 2011-11-02

    References (3)

  • Learning a Graphical Structure with Clusters  [in Japanese]

    HARA Satoshi , WASHIO Takashi

    電子情報通信学会技術研究報告. IBISML, 情報論的学習理論と機械学習 = IEICE technical report. IBISML, Information-based induction sciences and machine learning 111(275), 19-24, 2011-11-02

    References (18)

  • Learning an Invariant Substructure of Multiple Graphical Gaussian Models  [in Japanese]

    HARA Satoshi , WASHIO Takashi

    … In this paper, we propose a learning algorithm for finding such a common dependency structure from multiple datasets in the case of Gaussian Graphical Model (GGM). …

    IEICE technical report 110(476), 177-181, 2011-03-21

    References (14)

  • SIGN: LARGE-SCALE GENE NETWORK ESTIMATION ENVIRONMENT FOR HIGH PERFORMANCE COMPUTING

    TAMADA YOSHINORI , SHIMAMURA TEPPEI , YAMAGUCHI RUI , IMOTO SEIYA , NAGASAKI MASAO , MIYANO SATORU

    … In these three programs, five different models are available: static and dynamic nonparametric Bayesian networks, state space models, graphical Gaussian models, and vector autoregressive models. …

    Genome Informatics 25(1), 40-52, 2011

    J-STAGE 

  • Gene set-level network anaysis using a toxicogenomics database  [in Japanese]

    KIYOSAWA Naoki , YAMOTO Takashi , NIINO Noriyo , WATANABE Kyoko , MANABE Sunao , SANBUISSHO Atsushi , ONO Atsushi , YAMADA Hiroshi , URUSHIDANI Tetsuro , OONO Yasuo

    … 遺伝子セットの発現変動レベルは,薬物代謝酵素,グルタチオン枯渇応答遺伝子,がん原性関連遺伝子などの計58種類の遺伝子セットに関するD-score(Toxicol Lett 2009 188(2):91-7)計算により評価し,ネットワーク構造推定にはGaussian graphical modelを用いた。 …

    Annual Meeting of the Japanese Society of Toxicology 37(0), 243-243, 2010

    J-STAGE 

  • Characterization of Single Factor Models through Undirected Independence Graphs and Its Application  [in Japanese]

    KUROKI Manabu , WATANABE Souto

    … In this paper, we assume a Gaussian single factor model whose inverse covariance matrix of error variables is block diagonalized. … Then, we clarify the correspondent relationships between a single factor model and a set of undirected independence graphs. …

    Journal of The Japanese Society for Quality Control 40(2), 211-224, 2010

    J-STAGE  References (22)

  • Exact Inference in Discontinuous Firing Rate Estimation Using Belief Propagation

    TAKIYAMA Ken , KATAHIRA Kentaro , OKADA Masato

    Journal of the Physical Society of Japan 78(6), "064003-1"-"064003-5", 2009-06-15

    References (27)

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