Matches in SemOpenAlex for { <https://semopenalex.org/work/W4382051288> ?p ?o ?g. }
- W4382051288 endingPage "126496" @default.
- W4382051288 startingPage "126496" @default.
- W4382051288 abstract "Unsupervised dimensionality reduction (DR) aims to preserve input data structure in a low-dimensional (LD) space based on neighborhood information. In contrast, supervised DR intends to improve the learning performance, i.e., classification and regression, in an LD representation. Unfortunately, obtaining the complete label outputs of a data set for real-world applications is hard. Here, we introduce a novel DR framework coupling both available class labels and input feature similarities to extend the well-known t-distributed Stochastic Neighbor Embedding (SNE) for semi-supervised scenarios. Our proposal, termed Semi-Supervised t-SNE (SS.t-SNE), properly fixes the widths of Gaussian neighborhoods to reveal the salient local and global data structures in an LD space. Indeed, our approach is presented as a generalization of unsupervised and supervised versions of t-SNE. SS.t-SNE outperforms other semi-supervised DR methods in data visualization and classification tasks in LD embeddings." @default.
- W4382051288 created "2023-06-27" @default.
- W4382051288 creator A5007892780 @default.
- W4382051288 creator A5009959388 @default.
- W4382051288 creator A5018832028 @default.
- W4382051288 creator A5051246446 @default.
- W4382051288 creator A5057792577 @default.
- W4382051288 creator A5070860957 @default.
- W4382051288 date "2023-09-01" @default.
- W4382051288 modified "2023-10-05" @default.
- W4382051288 title "Semi-supervised t-SNE with multi-scale neighborhood preservation" @default.
- W4382051288 cites W1490414702 @default.
- W4382051288 cites W1529920312 @default.
- W4382051288 cites W1564277727 @default.
- W4382051288 cites W1587559447 @default.
- W4382051288 cites W1969204685 @default.
- W4382051288 cites W1993436046 @default.
- W4382051288 cites W1997780235 @default.
- W4382051288 cites W2001141328 @default.
- W4382051288 cites W2008968845 @default.
- W4382051288 cites W2013736751 @default.
- W4382051288 cites W2019176983 @default.
- W4382051288 cites W2020984122 @default.
- W4382051288 cites W2030818161 @default.
- W4382051288 cites W2053186076 @default.
- W4382051288 cites W2057491655 @default.
- W4382051288 cites W2065671342 @default.
- W4382051288 cites W2067752346 @default.
- W4382051288 cites W2092516120 @default.
- W4382051288 cites W2112796928 @default.
- W4382051288 cites W2113590298 @default.
- W4382051288 cites W2115622455 @default.
- W4382051288 cites W2118804324 @default.
- W4382051288 cites W2134312057 @default.
- W4382051288 cites W2139871091 @default.
- W4382051288 cites W2169507824 @default.
- W4382051288 cites W2171898484 @default.
- W4382051288 cites W2235688562 @default.
- W4382051288 cites W2293118840 @default.
- W4382051288 cites W2467197661 @default.
- W4382051288 cites W2532184334 @default.
- W4382051288 cites W2550999023 @default.
- W4382051288 cites W2662639535 @default.
- W4382051288 cites W2763633631 @default.
- W4382051288 cites W2795283445 @default.
- W4382051288 cites W2805627121 @default.
- W4382051288 cites W2807201128 @default.
- W4382051288 cites W2944219475 @default.
- W4382051288 cites W2988837181 @default.
- W4382051288 cites W2990200213 @default.
- W4382051288 cites W3028629919 @default.
- W4382051288 cites W3043327744 @default.
- W4382051288 cites W3089160504 @default.
- W4382051288 cites W3093598320 @default.
- W4382051288 cites W3105146463 @default.
- W4382051288 cites W3127452014 @default.
- W4382051288 cites W3127821930 @default.
- W4382051288 cites W4285545414 @default.
- W4382051288 cites W604641781 @default.
- W4382051288 doi "https://doi.org/10.1016/j.neucom.2023.126496" @default.
- W4382051288 hasPublicationYear "2023" @default.
- W4382051288 type Work @default.
- W4382051288 citedByCount "0" @default.
- W4382051288 crossrefType "journal-article" @default.
- W4382051288 hasAuthorship W4382051288A5007892780 @default.
- W4382051288 hasAuthorship W4382051288A5009959388 @default.
- W4382051288 hasAuthorship W4382051288A5018832028 @default.
- W4382051288 hasAuthorship W4382051288A5051246446 @default.
- W4382051288 hasAuthorship W4382051288A5057792577 @default.
- W4382051288 hasAuthorship W4382051288A5070860957 @default.
- W4382051288 hasConcept C119857082 @default.
- W4382051288 hasConcept C121332964 @default.
- W4382051288 hasConcept C134306372 @default.
- W4382051288 hasConcept C136389625 @default.
- W4382051288 hasConcept C138885662 @default.
- W4382051288 hasConcept C153180895 @default.
- W4382051288 hasConcept C154945302 @default.
- W4382051288 hasConcept C163716315 @default.
- W4382051288 hasConcept C177148314 @default.
- W4382051288 hasConcept C177264268 @default.
- W4382051288 hasConcept C199360897 @default.
- W4382051288 hasConcept C2776401178 @default.
- W4382051288 hasConcept C2780719617 @default.
- W4382051288 hasConcept C33923547 @default.
- W4382051288 hasConcept C41008148 @default.
- W4382051288 hasConcept C41608201 @default.
- W4382051288 hasConcept C41895202 @default.
- W4382051288 hasConcept C50644808 @default.
- W4382051288 hasConcept C58489278 @default.
- W4382051288 hasConcept C58973888 @default.
- W4382051288 hasConcept C62520636 @default.
- W4382051288 hasConcept C70518039 @default.
- W4382051288 hasConcept C83665646 @default.
- W4382051288 hasConceptScore W4382051288C119857082 @default.
- W4382051288 hasConceptScore W4382051288C121332964 @default.
- W4382051288 hasConceptScore W4382051288C134306372 @default.
- W4382051288 hasConceptScore W4382051288C136389625 @default.
- W4382051288 hasConceptScore W4382051288C138885662 @default.