DocumentCode
148980
Title
On the need for metrics in dictionary learning assessment
Author
Chevallier, Sylvain ; Barthelemy, Quentin ; Atif, Jamal
Author_Institution
LISV, Univ. of Versailles, Versailles, France
fYear
2014
fDate
1-5 Sept. 2014
Firstpage
1427
Lastpage
1431
Abstract
Dictionary-based approaches are the focus of a growing attention in the signal processing community, often achieving state of the art results in several application fields. Albeit their success, the criteria introduced so far for the assessment of their performances suffer from several shortcomings. The scope of this paper is to conduct a thorough analysis of these criteria and to highlight the need for principled criteria, enjoying the properties of metrics. Henceforth we introduce new criteria based on transportation like metrics and discuss their behaviors w.r.t the literature.
Keywords
learning (artificial intelligence); signal processing; dictionary learning assessment; signal processing community; Atomic measurements; Convergence; Dictionaries; Signal to noise ratio; Training; Transportation; Dictionary learning; detection rate; dictionary recovering; metric; transportation distance;
fLanguage
English
Publisher
ieee
Conference_Titel
Signal Processing Conference (EUSIPCO), 2014 Proceedings of the 22nd European
Conference_Location
Lisbon
Type
conf
Filename
6952505
Link To Document