FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W2804016075> ?p ?o ?g. }

• W2804016075 endingPage "6291" @default.
• W2804016075 startingPage "6276" @default.
• W2804016075 abstract "For dimension reduction on multiview data, most of the previous studies implicitly take an assumption that all samples are completed in all views. Nevertheless, this assumption could often be violated in real applications due to the presence of noise, limited access to data, equipment malfunction, and so on. Most of the previous methods will cease to work when missing values in one or multiple views occur, thus an incomplete-data oriented dimension reduction becomes an important issue. To this end, we mathematically formulate the above-mentioned issue as sparse low-rank representation through multiview subspace (SRRS) learning to impute missing values, by jointly measuring intraview relations (via sparse low-rank representation) and interview relations (through common subspace representation). Moreover, by exploiting various subspace priors in the proposed SRRS formulation, we develop three novel dimension reduction methods for incomplete multiview data: 1) multiview subspace learning via graph embedding; 2) multiview subspace learning via structured sparsity; and 3) sparse multiview feature selection via rank minimization. For each of them, the objective function and the algorithm to solve the resulting optimization problem are elaborated, respectively. We perform extensive experiments to investigate their performance on three types of tasks including data recovery, clustering, and classification. Both two toy examples (i.e., Swiss roll and S-curve) and four real-world data sets (i.e., face images, multisource news, multicamera activity, and multimodality neuroimaging data) are systematically tested. As demonstrated, our methods achieve the performance superior to that of the state-of-the-art comparable methods. Also, the results clearly show the advantage of integrating the sparsity and low-rankness over using each of them separately." @default.
• W2804016075 created "2018-06-01" @default.
• W2804016075 creator A5000494615 @default.
• W2804016075 creator A5041791232 @default.
• W2804016075 creator A5055917015 @default.
• W2804016075 creator A5074250521 @default.
• W2804016075 creator A5078658353 @default.
• W2804016075 date "2018-12-01" @default.
• W2804016075 modified "2023-10-14" @default.
• W2804016075 title "Incomplete-Data Oriented Multiview Dimension Reduction via Sparse Low-Rank Representation" @default.
• W2804016075 cites W1487602158 @default.
• W2804016075 cites W1937059634 @default.
• W2804016075 cites W1948350624 @default.
• W2804016075 cites W1972010412 @default.
• W2804016075 cites W1972441438 @default.
• W2804016075 cites W1996978148 @default.
• W2804016075 cites W1997201895 @default.
• W2804016075 cites W2007786430 @default.
• W2804016075 cites W2008340903 @default.
• W2804016075 cites W2010243644 @default.
• W2804016075 cites W2013076218 @default.
• W2804016075 cites W2035128422 @default.
• W2804016075 cites W2037549374 @default.
• W2804016075 cites W2037664838 @default.
• W2804016075 cites W2056486364 @default.
• W2804016075 cites W2070812954 @default.
• W2804016075 cites W2071207147 @default.
• W2804016075 cites W2079666190 @default.
• W2804016075 cites W2089494389 @default.
• W2804016075 cites W2090101874 @default.
• W2804016075 cites W2091711928 @default.
• W2804016075 cites W2097622337 @default.
• W2804016075 cites W2100556411 @default.
• W2804016075 cites W2103972604 @default.
• W2804016075 cites W2110355775 @default.
• W2804016075 cites W2112280891 @default.
• W2804016075 cites W2129496455 @default.
• W2804016075 cites W2129812935 @default.
• W2804016075 cites W2134789674 @default.
• W2804016075 cites W2135046866 @default.
• W2804016075 cites W2142674578 @default.
• W2804016075 cites W2145406564 @default.
• W2804016075 cites W2145962650 @default.
• W2804016075 cites W2146512693 @default.
• W2804016075 cites W2154053567 @default.
• W2804016075 cites W2156135524 @default.
• W2804016075 cites W2159001013 @default.
• W2804016075 cites W2328317224 @default.
• W2804016075 cites W2344457357 @default.
• W2804016075 cites W2398606097 @default.
• W2804016075 cites W2407812036 @default.
• W2804016075 cites W2476608201 @default.
• W2804016075 cites W2588822028 @default.
• W2804016075 cites W2746943580 @default.
• W2804016075 cites W4292363360 @default.
• W2804016075 doi "https://doi.org/10.1109/tnnls.2018.2828699" @default.
• W2804016075 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/29994545" @default.
• W2804016075 hasPublicationYear "2018" @default.
• W2804016075 type Work @default.
• W2804016075 sameAs 2804016075 @default.
• W2804016075 citedByCount "25" @default.
• W2804016075 countsByYear W28040160752019 @default.
• W2804016075 countsByYear W28040160752020 @default.
• W2804016075 countsByYear W28040160752021 @default.
• W2804016075 countsByYear W28040160752022 @default.
• W2804016075 countsByYear W28040160752023 @default.
• W2804016075 crossrefType "journal-article" @default.
• W2804016075 hasAuthorship W2804016075A5000494615 @default.
• W2804016075 hasAuthorship W2804016075A5041791232 @default.
• W2804016075 hasAuthorship W2804016075A5055917015 @default.
• W2804016075 hasAuthorship W2804016075A5074250521 @default.
• W2804016075 hasAuthorship W2804016075A5078658353 @default.
• W2804016075 hasConcept C114614502 @default.
• W2804016075 hasConcept C119857082 @default.
• W2804016075 hasConcept C124066611 @default.
• W2804016075 hasConcept C132525143 @default.
• W2804016075 hasConcept C153180895 @default.
• W2804016075 hasConcept C154945302 @default.
• W2804016075 hasConcept C160920958 @default.
• W2804016075 hasConcept C163294075 @default.
• W2804016075 hasConcept C164226766 @default.
• W2804016075 hasConcept C17744445 @default.
• W2804016075 hasConcept C199539241 @default.
• W2804016075 hasConcept C202444582 @default.
• W2804016075 hasConcept C2776359362 @default.
• W2804016075 hasConcept C32834561 @default.
• W2804016075 hasConcept C33676613 @default.
• W2804016075 hasConcept C33923547 @default.
• W2804016075 hasConcept C41008148 @default.
• W2804016075 hasConcept C41608201 @default.
• W2804016075 hasConcept C70518039 @default.
• W2804016075 hasConcept C80444323 @default.
• W2804016075 hasConcept C9357733 @default.
• W2804016075 hasConcept C94625758 @default.
• W2804016075 hasConceptScore W2804016075C114614502 @default.
• W2804016075 hasConceptScore W2804016075C119857082 @default.
• W2804016075 hasConceptScore W2804016075C124066611 @default.
• W2804016075 hasConceptScore W2804016075C132525143 @default.

• next