Matches in SemOpenAlex for { <https://semopenalex.org/work/W2084028080> ?p ?o ?g. }
- W2084028080 endingPage "2150" @default.
- W2084028080 startingPage "2138" @default.
- W2084028080 abstract "Many pattern analysis and data mining problems have witnessed high-dimensional data represented by a large number of features, which are often redundant and noisy. Feature selection is one main technique for dimensionality reduction that involves identifying a subset of the most useful features. In this paper, a novel unsupervised feature selection algorithm, named clustering-guided sparse structural learning (CGSSL), is proposed by integrating cluster analysis and sparse structural analysis into a joint framework and experimentally evaluated. Nonnegative spectral clustering is developed to learn more accurate cluster labels of the input samples, which guide feature selection simultaneously. Meanwhile, the cluster labels are also predicted by exploiting the hidden structure shared by different features, which can uncover feature correlations to make the results more reliable. Row-wise sparse models are leveraged to make the proposed model suitable for feature selection. To optimize the proposed formulation, we propose an efficient iterative algorithm. Finally, extensive experiments are conducted on 12 diverse benchmarks, including face data, handwritten digit data, document data, and biomedical data. The encouraging experimental results in comparison with several representative algorithms and the theoretical analysis demonstrate the efficiency and effectiveness of the proposed algorithm for feature selection." @default.
- W2084028080 created "2016-06-24" @default.
- W2084028080 creator A5005421447 @default.
- W2084028080 creator A5009348332 @default.
- W2084028080 creator A5011384237 @default.
- W2084028080 creator A5017096005 @default.
- W2084028080 creator A5089784582 @default.
- W2084028080 date "2014-09-01" @default.
- W2084028080 modified "2023-10-01" @default.
- W2084028080 title "Clustering-Guided Sparse Structural Learning for Unsupervised Feature Selection" @default.
- W2084028080 cites W12820539 @default.
- W2084028080 cites W1500895378 @default.
- W2084028080 cites W1902027874 @default.
- W2084028080 cites W1968178977 @default.
- W2084028080 cites W1980945904 @default.
- W2084028080 cites W1986691909 @default.
- W2084028080 cites W2004646046 @default.
- W2084028080 cites W2020804487 @default.
- W2084028080 cites W2042759724 @default.
- W2084028080 cites W2060542593 @default.
- W2084028080 cites W2070959357 @default.
- W2084028080 cites W2096044434 @default.
- W2084028080 cites W2102831150 @default.
- W2084028080 cites W2120000263 @default.
- W2084028080 cites W2121410881 @default.
- W2084028080 cites W2121947440 @default.
- W2084028080 cites W2126185804 @default.
- W2084028080 cites W2128873747 @default.
- W2084028080 cites W2129793592 @default.
- W2084028080 cites W2132379769 @default.
- W2084028080 cites W2142623955 @default.
- W2084028080 cites W2144276987 @default.
- W2084028080 cites W2148633389 @default.
- W2084028080 cites W2149870286 @default.
- W2084028080 cites W2154053567 @default.
- W2084028080 cites W2158933803 @default.
- W2084028080 cites W2159611475 @default.
- W2084028080 doi "https://doi.org/10.1109/tkde.2013.65" @default.
- W2084028080 hasPublicationYear "2014" @default.
- W2084028080 type Work @default.
- W2084028080 sameAs 2084028080 @default.
- W2084028080 citedByCount "224" @default.
- W2084028080 countsByYear W20840280802013 @default.
- W2084028080 countsByYear W20840280802014 @default.
- W2084028080 countsByYear W20840280802015 @default.
- W2084028080 countsByYear W20840280802016 @default.
- W2084028080 countsByYear W20840280802017 @default.
- W2084028080 countsByYear W20840280802018 @default.
- W2084028080 countsByYear W20840280802019 @default.
- W2084028080 countsByYear W20840280802020 @default.
- W2084028080 countsByYear W20840280802021 @default.
- W2084028080 countsByYear W20840280802022 @default.
- W2084028080 countsByYear W20840280802023 @default.
- W2084028080 crossrefType "journal-article" @default.
- W2084028080 hasAuthorship W2084028080A5005421447 @default.
- W2084028080 hasAuthorship W2084028080A5009348332 @default.
- W2084028080 hasAuthorship W2084028080A5011384237 @default.
- W2084028080 hasAuthorship W2084028080A5017096005 @default.
- W2084028080 hasAuthorship W2084028080A5089784582 @default.
- W2084028080 hasConcept C119857082 @default.
- W2084028080 hasConcept C124101348 @default.
- W2084028080 hasConcept C138885662 @default.
- W2084028080 hasConcept C148483581 @default.
- W2084028080 hasConcept C153180895 @default.
- W2084028080 hasConcept C154945302 @default.
- W2084028080 hasConcept C184509293 @default.
- W2084028080 hasConcept C2776401178 @default.
- W2084028080 hasConcept C41008148 @default.
- W2084028080 hasConcept C41895202 @default.
- W2084028080 hasConcept C59404180 @default.
- W2084028080 hasConcept C70518039 @default.
- W2084028080 hasConcept C73555534 @default.
- W2084028080 hasConcept C8038995 @default.
- W2084028080 hasConcept C81917197 @default.
- W2084028080 hasConceptScore W2084028080C119857082 @default.
- W2084028080 hasConceptScore W2084028080C124101348 @default.
- W2084028080 hasConceptScore W2084028080C138885662 @default.
- W2084028080 hasConceptScore W2084028080C148483581 @default.
- W2084028080 hasConceptScore W2084028080C153180895 @default.
- W2084028080 hasConceptScore W2084028080C154945302 @default.
- W2084028080 hasConceptScore W2084028080C184509293 @default.
- W2084028080 hasConceptScore W2084028080C2776401178 @default.
- W2084028080 hasConceptScore W2084028080C41008148 @default.
- W2084028080 hasConceptScore W2084028080C41895202 @default.
- W2084028080 hasConceptScore W2084028080C59404180 @default.
- W2084028080 hasConceptScore W2084028080C70518039 @default.
- W2084028080 hasConceptScore W2084028080C73555534 @default.
- W2084028080 hasConceptScore W2084028080C8038995 @default.
- W2084028080 hasConceptScore W2084028080C81917197 @default.
- W2084028080 hasIssue "9" @default.
- W2084028080 hasLocation W20840280801 @default.
- W2084028080 hasOpenAccess W2084028080 @default.
- W2084028080 hasPrimaryLocation W20840280801 @default.
- W2084028080 hasRelatedWork W2139206670 @default.
- W2084028080 hasRelatedWork W2266203484 @default.
- W2084028080 hasRelatedWork W2292254049 @default.
- W2084028080 hasRelatedWork W2385233088 @default.
- W2084028080 hasRelatedWork W2546942002 @default.