FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W4319866346> ?p ?o ?g. }

• W4319866346 endingPage "4189" @default.
• W4319866346 startingPage "4177" @default.
• W4319866346 abstract "Self-representation subspace clustering based on graphs has the merits of capability and efficiency. However, the graph built by the self-representation methods has two issues: (i) usually lacking conciseness and informativeness due to the negative representation coefficients. (ii) no guarantee of an overall optimal solution due to the separation of representation learning and graph construction. To alleviate these issues, we propose a novel subspace clustering via learning non-negative representation with an adaptive graph. Specifically, we explicitly impose the non-negative constraint on the self-representation learning, ensuring that each data point is approximated from a group of homogeneous samples and enhancing the distinguishability of data representation. Meanwhile, an adaptive graph is developed so that both representation and the geometric structure of data are simultaneously learned in a unified procedure. Moreover, the learned representation is less sensitive to data noise imposed by the <inline-formula xmlns:mml=http://www.w3.org/1998/Math/MathML xmlns:xlink=http://www.w3.org/1999/xlink> <tex-math notation=LaTeX>$ell _{2,1}$ </tex-math></inline-formula> -norm, so the adaptive graph will be further improved. An efficient optimization procedure is developed to find the optimal solution. Extensive experiments on subspace clustering and the extension application to image segmentation validate the advantages of our method against state-of-the-art methods." @default.
• W4319866346 created "2023-02-11" @default.
• W4319866346 creator A5056087679 @default.
• W4319866346 creator A5070931010 @default.
• W4319866346 creator A5083774648 @default.
• W4319866346 creator A5090591934 @default.
• W4319866346 date "2023-08-01" @default.
• W4319866346 modified "2023-10-15" @default.
• W4319866346 title "Subspace Clustering via Adaptive Non-Negative Representation Learning and Its Application to Image Segmentation" @default.
• W4319866346 cites W1600471557 @default.
• W4319866346 cites W1884731728 @default.
• W4319866346 cites W1890623278 @default.
• W4319866346 cites W1902027874 @default.
• W4319866346 cites W1944071515 @default.
• W4319866346 cites W1993962865 @default.
• W4319866346 cites W1997201895 @default.
• W4319866346 cites W2006533296 @default.
• W4319866346 cites W2035128422 @default.
• W4319866346 cites W2037549374 @default.
• W4319866346 cites W2052575990 @default.
• W4319866346 cites W2065220650 @default.
• W4319866346 cites W2079361215 @default.
• W4319866346 cites W2085013758 @default.
• W4319866346 cites W2088025572 @default.
• W4319866346 cites W2107799335 @default.
• W4319866346 cites W2108119513 @default.
• W4319866346 cites W2121927366 @default.
• W4319866346 cites W2140245639 @default.
• W4319866346 cites W2142827986 @default.
• W4319866346 cites W2144359569 @default.
• W4319866346 cites W2153320597 @default.
• W4319866346 cites W2162316550 @default.
• W4319866346 cites W2197707282 @default.
• W4319866346 cites W2240559667 @default.
• W4319866346 cites W2262946425 @default.
• W4319866346 cites W2295124130 @default.
• W4319866346 cites W2405933695 @default.
• W4319866346 cites W2468752595 @default.
• W4319866346 cites W2577472518 @default.
• W4319866346 cites W2592859786 @default.
• W4319866346 cites W2782747699 @default.
• W4319866346 cites W2802754347 @default.
• W4319866346 cites W2898233200 @default.
• W4319866346 cites W2905621769 @default.
• W4319866346 cites W2906217954 @default.
• W4319866346 cites W2963165461 @default.
• W4319866346 cites W2963840432 @default.
• W4319866346 cites W2965477817 @default.
• W4319866346 cites W2981305139 @default.
• W4319866346 cites W2983762999 @default.
• W4319866346 cites W2994051615 @default.
• W4319866346 cites W3000116636 @default.
• W4319866346 cites W3025752507 @default.
• W4319866346 cites W3026594100 @default.
• W4319866346 cites W3031414651 @default.
• W4319866346 cites W3082753413 @default.
• W4319866346 cites W3087124270 @default.
• W4319866346 cites W3087781490 @default.
• W4319866346 cites W3088663932 @default.
• W4319866346 cites W3091687261 @default.
• W4319866346 cites W3091857251 @default.
• W4319866346 cites W3099183477 @default.
• W4319866346 cites W3111614038 @default.
• W4319866346 cites W3112808477 @default.
• W4319866346 cites W3121769020 @default.
• W4319866346 cites W3122581893 @default.
• W4319866346 cites W3128918602 @default.
• W4319866346 cites W3132532642 @default.
• W4319866346 cites W4200226646 @default.
• W4319866346 cites W4206441147 @default.
• W4319866346 cites W4220873374 @default.
• W4319866346 cites W4283391360 @default.
• W4319866346 cites W4283797473 @default.
• W4319866346 cites W4284968770 @default.
• W4319866346 cites W4292363360 @default.
• W4319866346 cites W4296311555 @default.
• W4319866346 cites W4301283118 @default.
• W4319866346 doi "https://doi.org/10.1109/tcsvt.2023.3241172" @default.
• W4319866346 hasPublicationYear "2023" @default.
• W4319866346 type Work @default.
• W4319866346 citedByCount "0" @default.
• W4319866346 crossrefType "journal-article" @default.
• W4319866346 hasAuthorship W4319866346A5056087679 @default.
• W4319866346 hasAuthorship W4319866346A5070931010 @default.
• W4319866346 hasAuthorship W4319866346A5083774648 @default.
• W4319866346 hasAuthorship W4319866346A5090591934 @default.
• W4319866346 hasConcept C132525143 @default.
• W4319866346 hasConcept C153180895 @default.
• W4319866346 hasConcept C154945302 @default.
• W4319866346 hasConcept C17744445 @default.
• W4319866346 hasConcept C199539241 @default.
• W4319866346 hasConcept C21080849 @default.
• W4319866346 hasConcept C2776359362 @default.
• W4319866346 hasConcept C32834561 @default.
• W4319866346 hasConcept C33923547 @default.
• W4319866346 hasConcept C41008148 @default.
• W4319866346 hasConcept C59404180 @default.
• W4319866346 hasConcept C73555534 @default.

• next