Structured Tensor-Train Decomposition for ...
Document type :
Partie d'ouvrage
Title :
Structured Tensor-Train Decomposition for Speeding-Up Kernel-Based Learning
Author(s) :
Zniyed, Yassine [Auteur]
Université de Toulon - École d’ingénieurs SeaTech [UTLN SeaTech]
Signal et Image [SIIM]
Karmouda, Ouafae [Auteur]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Boulanger, Jérémie [Auteur]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Boyer, Remy [Auteur]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
de Almeida, André L. F. [Auteur]
Wireless Telecom Research Group [Fortaleza] [GTEL]
Favier, Gérard [Auteur]
Signal, Images et Systèmes [Laboratoire I3S - SIS]
Université de Toulon - École d’ingénieurs SeaTech [UTLN SeaTech]
Signal et Image [SIIM]
Karmouda, Ouafae [Auteur]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Boulanger, Jérémie [Auteur]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Boyer, Remy [Auteur]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
de Almeida, André L. F. [Auteur]
Wireless Telecom Research Group [Fortaleza] [GTEL]
Favier, Gérard [Auteur]
Signal, Images et Systèmes [Laboratoire I3S - SIS]
Scientific editor(s) :
Yipeng Liu
Book title :
Tensors for Data Processing
Publisher :
Elsevier
Publication date :
2021
English keyword(s) :
HOSVD
Classification
Tensor Trains
Tucker decomposition
Structured Tensors
Classification
Tensor Trains
Tucker decomposition
Structured Tensors
HAL domain(s) :
Mathématiques [math]
Sciences de l'ingénieur [physics]
Sciences de l'ingénieur [physics]
English abstract : [en]
In this chapter, we present an algebraic relation between the Tucker model and the Tensor-Train decomposition with structured cores. Exploiting this link, we present a new fast algorithm to compute the dominant singular ...
Show more >In this chapter, we present an algebraic relation between the Tucker model and the Tensor-Train decomposition with structured cores. Exploiting this link, we present a new fast algorithm to compute the dominant singular subspaces of a Q-order tensor. As opposedt o the state of the art methods (usually called HOSVD for high-order SVD), our approach mitigates the well-known “curse of dimentionality”. This approach is applied to speed up kernel-based supervised tensor classification.Show less >
Show more >In this chapter, we present an algebraic relation between the Tucker model and the Tensor-Train decomposition with structured cores. Exploiting this link, we present a new fast algorithm to compute the dominant singular subspaces of a Q-order tensor. As opposedt o the state of the art methods (usually called HOSVD for high-order SVD), our approach mitigates the well-known “curse of dimentionality”. This approach is applied to speed up kernel-based supervised tensor classification.Show less >
Language :
Anglais
Audience :
Internationale
Popular science :
Non
Collections :
Source :