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Paper Abstract and Keywords
Presentation 2013-08-29 16:10
[Tutorial Lecture] Tensor-Based Machine Learning: Modeling, Algorithms and Applications
Qibin Zhao, Andrzej Cichocki (RIKEN) SIP2013-73
Abstract (in Japanese) (See Japanese page) 
(in English) Tensors are a generalization of vectors and matrices to higher dimensions that can naturally represent the multidimensional structured data. Based on multilinear algebra, tensor factorizations enable us to effectively capture the hidden structure of the data, which is usually available as a priori information on the data nature. Hence it attracts much interest on unsupervised learning and data exploratory. In this paper, we firstly present some basic concept of tensor factorization and multilinear algebra, then a novel framework for tensor variate Gaussian processes (GP) regression is introduced, which exploits a covariance function defined on tensor representation of data inputs. In this way, we bring together the powerful GP methods supported by Bayesian inference and higher-order tensor analysis techniques into one framework. This enables us to account for the underlying data structure within the model, providing a powerful framework for structural data analysis, such as 3D video sequences. Simulation results on both the synthetic data and a real world application of estimating the crowd size in videos, without the necessarity of the typical segmentations and feature extractions, demonstrate the effectiveness of the proposed approach.
Keyword (in Japanese) (See Japanese page) 
(in English) Tensor factorization / multilinear algebra / Gaussian processes / kernel methods / / / /  
Reference Info. IEICE Tech. Rep., vol. 113, no. 191, SIP2013-73, pp. 35-40, Aug. 2013.
Paper # SIP2013-73 
Date of Issue 2013-08-22 (SIP) 
ISSN Print edition: ISSN 0913-5685  Online edition: ISSN 2432-6380
Download PDF SIP2013-73

Conference Information
Committee SIP  
Conference Date 2013-08-29 - 2013-08-30 
Place (in Japanese) (See Japanese page) 
Place (in English) Tokyo University of Agriculture and Technology 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Image processing and related topics 
Paper Information
Registration To SIP 
Conference Code 2013-08-SIP 
Language English 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Tensor-Based Machine Learning: Modeling, Algorithms and Applications 
Sub Title (in English)  
Keyword(1) Tensor factorization  
Keyword(2) multilinear algebra  
Keyword(3) Gaussian processes  
Keyword(4) kernel methods  
1st Author's Name Qibin Zhao  
1st Author's Affiliation RIKEN (RIKEN)
2nd Author's Name Andrzej Cichocki  
2nd Author's Affiliation RIKEN (RIKEN)
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Date Time 2013-08-29 16:10:00 
Presentation Time 60 
Registration for SIP 
Paper # IEICE-SIP2013-73 
Volume (vol) IEICE-113 
Number (no) no.191 
Page pp.35-40 
#Pages IEICE-6 
Date of Issue IEICE-SIP-2013-08-22 

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