PDF-Mean and covariance models for tensor valued data

Author : faustina-dinatale | Published Date : 2017-03-30

Modelingmeanstructure ModelingcovariancestructureOutline IntroductionandexamplesModelingmeanstructurereducedrankarraysviaPARAFACleastsquaresversusmodelbasedPARAFACorderedprobitPARAFACModelingcovaria

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Mean and covariance models for tensor valued data: Transcript

Modelingmeanstructure ModelingcovariancestructureOutline IntroductionandexamplesModelingmeanstructurereducedrankarraysviaPARAFACleastsquaresversusmodelbasedPARAFACorderedprobitPARAFACModelingcovaria. IndexTopicarraytensor,1%*t%(tensor),1%t*%(tensor),1%t*t%(tensor),1aperm,2matmult,2tensor,14 J. Friedman, T. Hastie, R. . Tibshirani. Biostatistics, 2008. Presented by . Minhua. Chen. 1. Motivation. Mathematical Model. Mathematical Tools. Graphical LASSO. Related papers. 2. Outline. Motivation. He Zhang. 1. , He Huang. 2. , . Rui. Li. 1. , . Jie. Chen. 1. , Li-Shi Luo. 2. Jefferson Lab. Old Dominion University. FEIS-2, 05/15/2015. Outline. He Zhang. ---. 3. ---. Introduction of FMM. He Zhang. Overview. Theory. Basic . physics. Tensor. Diffusion . imaging . Practice. How . do you do DTI?. . Tractography. . DTI . in . FSL and other programs. Diffusion . Tensor Imaging. Brownian motion. Shenghan Jiang. Boston College. Benasque. February. , 09, 2017. Symmetric tensor-networks and topological phases. Collaborators:. Ying Ran (Boston College) . Panjin. Kim, . Hyungyong. Lee, Jung . Hoon. using Low-rank Tensor Data. Juan Andrés . Bazerque. , Gonzalo . Mateos. , and . Georgios. B. . Giannakis. . May 29. , 2013. . SPiNCOM. , University of Minnesota. . Acknowledgment: . AFOSR MURI grant no. FA 9550-10-1-0567. He Zhang. 1. , He Huang. 2. , . Rui. Li. 1. , . Jie. Chen. 1. , Li-Shi Luo. 2. Jefferson Lab. Old Dominion University. FEIS-2, 05/15/2015. Outline. He Zhang. ---. 3. ---. Introduction of FMM. He Zhang. Miriam Huntley. SEAS, Harvard University. May 15, 2013. 18.338 Course Project. RMT. Real World Data. “When it comes to RMT in the real world, we know close to nothing.”. -Prof. Alan . Edelman. , last week. . Data: . Semivariogram. and Covariance Analysis: . GRAD6104/8104 INES 8090. Spatial Statistic- Spring 2017. Geostatistics. . Image . source http://. www.nasa.gov/topics/earth/features/health-sapping.html. Author: Maximilian Nickel. Speaker: . Xinge. Wen. INTRODUCTION . –. Multi relational Data. Relational data is everywhere in our life:. WEB. Social networks. Bioinformatics. INTRODUCTION . –. Why Tensor . Overview. Theory. Basic . physics. Tensor. Diffusion . imaging . Practice. How . do you do DTI?. . Tractography. . DTI . in . FSL and other programs. Diffusion . Tensor Imaging. Brownian motion. Burba. , G., 2013. Eddy Covariance Method for Scientific, Industrial, Agricultural and Regulatory Applications: A Field Book on Measuring Ecosystem Gas Exchange and Areal Emission Rates. . LI-COR . Biosciences, Lincoln, . J. Friedman, T. Hastie, R. . Tibshirani. Biostatistics, 2008. Presented by . Minhua. Chen. 1. Motivation. Mathematical Model. Mathematical Tools. Graphical LASSO. Related papers. 2. Outline. Motivation. from . axion. -gauge couplings. Ippei. Obata (Kyoto University. , PhD. ). (in preparation). 29_Nov_. CosPA2016. Primordial GWs. . from the inflation. Energy scale of . early Universe. Red-tilted.. Parity-symmetric..

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