| dbo:abstract
|
- The in-crowd algorithm is a numerical method for solving basis pursuit denoising quickly; faster than any other algorithm for large, sparse problems. This algorithm is an active set method, which minimizes iteratively sub-problems of the global basis pursuit denoising: where is the observed signal, is the sparse signal to be recovered, is the expected signal under , and is the regularization parameter trading off signal fidelity and simplicity. The simplicity is here measured using the sparsity of the solution , measure through its -norm. The active set strategies are very efficient in this context as only few coefficient are expected to be non-zero. Thus, if they can be identified, solving the problem restricted to these coefficients yield the solution. Here, the features are greedily selected based on the absolute value of their gradient at the current estimate. Other active-set methods for the basis pursuit denoising includes BLITZ, where the selection of the active set is performed using the duality gap of the problem, and The Feature Sign Search, where the features are included based on the estimate of their sign. (en)
|
| dbo:wikiPageID
| |
| dbo:wikiPageLength
|
- 3451 (xsd:nonNegativeInteger)
|
| dbo:wikiPageRevisionID
| |
| dbo:wikiPageWikiLink
| |
| dbp:wikiPageUsesTemplate
| |
| dcterms:subject
| |
| rdfs:comment
|
- The in-crowd algorithm is a numerical method for solving basis pursuit denoising quickly; faster than any other algorithm for large, sparse problems. This algorithm is an active set method, which minimizes iteratively sub-problems of the global basis pursuit denoising: Other active-set methods for the basis pursuit denoising includes BLITZ, where the selection of the active set is performed using the duality gap of the problem, and The Feature Sign Search, where the features are included based on the estimate of their sign. (en)
|
| rdfs:label
| |
| owl:sameAs
| |
| prov:wasDerivedFrom
| |
| foaf:isPrimaryTopicOf
| |
| is dbo:wikiPageWikiLink
of | |
| is foaf:primaryTopic
of | |
