• Subspace Evolution and Transfe...

Treffer: Subspace Evolution and Transfer (SET) for Low-Rank Matrix Completion

Title:
Subspace Evolution and Transfer (SET) for Low-Rank Matrix Completion
Authors:
WEI DAI, MILENKOVIC, Olgica, KERMAN, Ely
Source:
IEEE transactions on signal processing. 59(7):3120-3132
Publisher Information:
New York, NY: Institute of Electrical and Electronics Engineers, 2011.
Publication Year:
2011
Physical Description:
print, 24 ref
Original Material:
INIST-CNRS
Subject Terms:
Telecommunications, Télécommunications, Sciences exactes et technologie, Exact sciences and technology, Sciences appliquees, Applied sciences, Telecommunications et theorie de l'information, Telecommunications and information theory, Théorie de l'information, du signal et des communications, Information, signal and communications theory, Théorie du signal et des communications, Signal and communications theory, Signal, bruit, Signal, noise, Détection, estimation, filtrage, égalisation, prédiction, Detection, estimation, filtering, equalization, prediction, Algorithme, Algorithm, Algoritmo, Evaluation performance, Performance evaluation, Evaluación prestación, Méthode descente, Descent method, Método descenso, Méthode gradient, Gradient method, Método gradiente, Méthode sous espace, Subspace method, Método subespacio, Programmation non convexe, Non convex programming, Programación no convexa, Taux échantillonnage, Sampling rate, Razón muestreo, Traitement signal, Signal processing, Procesamiento señal, Grassmann manifold, linear subspace, matrix completion, non-convex optimization
Document Type:
Fachzeitschrift Article
File Description:
text
Language:
English
Author Affiliations:
Department of Electrical and Electronic Engineering, Imperial College London, London SW7 2AZ, United Kingdom
Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, Urbana, IL 61801, United States
Department of Mathematics, University of Illinois at Urbana-Champaign, Urbana, IL 61801, United States
ISSN:
1053-587X
Access URL:
http://pascal-francis.inist.fr/vibad/index.php?action=search&terms=24285478
Rights:
Copyright 2015 INIST-CNRS
CC BY 4.0
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
Notes:
Telecommunications and information theory
Accession Number:
edscal.24285478
Database:
PASCAL Archive

Weitere Informationen

We describe a new algorithm, termed subspace evolution and transfer (SET), for solving consistent low-rank matrix completion problems. The algorithm takes as its input a subset of entries of a low-rank matrix and outputs one low-rank matrix consistent with the given observations. The completion task is accomplished by searching for a column space in the Grassmann manifold that matches the incomplete observations. The SET algorithm consists of two parts—subspace evolution and subspace transfer. In the evolution part, we use a gradient descent method on the Grassmann manifold to refine our estimate of the column space. Since the gradient descent algorithm is not guaranteed to converge due to the existence of barriers along the search path, we design a new mechanism for detecting barriers and transferring the estimated column space across the barriers. This mechanism constitutes the core of the transfer step of the algorithm. The SET algorithm exhibits excellent empirical performance for a large range of sampling rates.