Matches in SemOpenAlex for { <https://semopenalex.org/work/W2031770887> ?p ?o ?g. }
Showing items 1 to 87 of
87
with 100 items per page.
- W2031770887 endingPage "235" @default.
- W2031770887 startingPage "223" @default.
- W2031770887 abstract "This paper presents a fast algorithm called Column Generation Newton (CGN) for kernel 1-norm support vector machines (SVMs). CGN combines the Column Generation (CG) algorithm and the Newton Linear Programming SVM (NLPSVM) method. NLPSVM was proposed for solving 1-norm SVM, and CG is frequently used in large-scale integer and linear programming algorithms. In each iteration of the kernel 1-norm SVM, NLPSVM has a time complexity of O(ℓ3), where ℓ is the sample number, and CG has a time complexity between O(ℓ3) and O(n′3), where n′ is the number of columns of the coefficient matrix in the subproblem. CGN uses CG to generate a sequence of subproblems containing only active constraints and then NLPSVM to solve each subproblem. Since the subproblem in each iteration only consists of n′ unbound constraints, CGN thus has a time complexity of O(n′3), which is smaller than that of NLPSVM and CG. Also, CGN is faster than CG when the solution to 1-norm SVM is sparse. A theorem is given to show a finite step convergence of CGN. Experimental results on the Ringnorm and UCI data sets demonstrate the efficiency of CGN to solve the kernel 1-norm SVM." @default.
- W2031770887 created "2016-06-24" @default.
- W2031770887 creator A5066650945 @default.
- W2031770887 creator A5066716873 @default.
- W2031770887 date "2013-11-01" @default.
- W2031770887 modified "2023-09-24" @default.
- W2031770887 title "A fast algorithm for kernel 1-norm support vector machines" @default.
- W2031770887 cites W1578080815 @default.
- W2031770887 cites W1970355999 @default.
- W2031770887 cites W1993105429 @default.
- W2031770887 cites W2062071965 @default.
- W2031770887 cites W2081388083 @default.
- W2031770887 cites W2089631831 @default.
- W2031770887 cites W2091143818 @default.
- W2031770887 cites W2095885101 @default.
- W2031770887 cites W2111539174 @default.
- W2031770887 cites W2117526678 @default.
- W2031770887 cites W2138153214 @default.
- W2031770887 cites W2150039764 @default.
- W2031770887 cites W2153631847 @default.
- W2031770887 cites W2167403361 @default.
- W2031770887 doi "https://doi.org/10.1016/j.knosys.2013.08.008" @default.
- W2031770887 hasPublicationYear "2013" @default.
- W2031770887 type Work @default.
- W2031770887 sameAs 2031770887 @default.
- W2031770887 citedByCount "6" @default.
- W2031770887 countsByYear W20317708872014 @default.
- W2031770887 countsByYear W20317708872015 @default.
- W2031770887 countsByYear W20317708872017 @default.
- W2031770887 countsByYear W20317708872018 @default.
- W2031770887 countsByYear W20317708872019 @default.
- W2031770887 countsByYear W20317708872022 @default.
- W2031770887 crossrefType "journal-article" @default.
- W2031770887 hasAuthorship W2031770887A5066650945 @default.
- W2031770887 hasAuthorship W2031770887A5066716873 @default.
- W2031770887 hasConcept C11413529 @default.
- W2031770887 hasConcept C118615104 @default.
- W2031770887 hasConcept C121332964 @default.
- W2031770887 hasConcept C122280245 @default.
- W2031770887 hasConcept C12267149 @default.
- W2031770887 hasConcept C126255220 @default.
- W2031770887 hasConcept C154945302 @default.
- W2031770887 hasConcept C158693339 @default.
- W2031770887 hasConcept C17744445 @default.
- W2031770887 hasConcept C191795146 @default.
- W2031770887 hasConcept C199539241 @default.
- W2031770887 hasConcept C33923547 @default.
- W2031770887 hasConcept C41008148 @default.
- W2031770887 hasConcept C62520636 @default.
- W2031770887 hasConcept C74193536 @default.
- W2031770887 hasConcept C92207270 @default.
- W2031770887 hasConceptScore W2031770887C11413529 @default.
- W2031770887 hasConceptScore W2031770887C118615104 @default.
- W2031770887 hasConceptScore W2031770887C121332964 @default.
- W2031770887 hasConceptScore W2031770887C122280245 @default.
- W2031770887 hasConceptScore W2031770887C12267149 @default.
- W2031770887 hasConceptScore W2031770887C126255220 @default.
- W2031770887 hasConceptScore W2031770887C154945302 @default.
- W2031770887 hasConceptScore W2031770887C158693339 @default.
- W2031770887 hasConceptScore W2031770887C17744445 @default.
- W2031770887 hasConceptScore W2031770887C191795146 @default.
- W2031770887 hasConceptScore W2031770887C199539241 @default.
- W2031770887 hasConceptScore W2031770887C33923547 @default.
- W2031770887 hasConceptScore W2031770887C41008148 @default.
- W2031770887 hasConceptScore W2031770887C62520636 @default.
- W2031770887 hasConceptScore W2031770887C74193536 @default.
- W2031770887 hasConceptScore W2031770887C92207270 @default.
- W2031770887 hasLocation W20317708871 @default.
- W2031770887 hasOpenAccess W2031770887 @default.
- W2031770887 hasPrimaryLocation W20317708871 @default.
- W2031770887 hasRelatedWork W2018239771 @default.
- W2031770887 hasRelatedWork W2108697353 @default.
- W2031770887 hasRelatedWork W2127343225 @default.
- W2031770887 hasRelatedWork W2137362393 @default.
- W2031770887 hasRelatedWork W2169565408 @default.
- W2031770887 hasRelatedWork W2348982811 @default.
- W2031770887 hasRelatedWork W2361876834 @default.
- W2031770887 hasRelatedWork W2373430648 @default.
- W2031770887 hasRelatedWork W2736885024 @default.
- W2031770887 hasRelatedWork W3004569186 @default.
- W2031770887 hasVolume "52" @default.
- W2031770887 isParatext "false" @default.
- W2031770887 isRetracted "false" @default.
- W2031770887 magId "2031770887" @default.
- W2031770887 workType "article" @default.