FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W421912185> ?p ?o ?g. }

• W421912185 endingPage "45" @default.
• W421912185 startingPage "37" @default.
• W421912185 abstract "We consider the problem of clustering data points in high dimensions, i.e., when the number of data points may be much smaller than the number of dimensions. Specifically, we consider a Gaussian mixture model (GMM) with two non-spherical Gaussian components, where the clusters are distinguished by only a few relevant dimensions. The method we propose is a combination of a recent approach for learning parameters of a Gaussian mixture model and sparse linear discriminant analysis (LDA). In addition to cluster assignments, the method returns an estimate of the set of features relevant for clustering. Our results indicate that the sample complexity of clustering depends on the sparsity of the relevant feature set, while only scaling logarithmically with the ambient dimension. Further, we require much milder assumptions than existing work on clustering in high dimensions. In particular, we do not require spherical clusters nor necessitate mean separation along relevant dimensions." @default.
• W421912185 created "2016-06-24" @default.
• W421912185 creator A5062033062 @default.
• W421912185 creator A5073607469 @default.
• W421912185 creator A5077874981 @default.
• W421912185 date "2015-02-21" @default.
• W421912185 modified "2023-09-22" @default.
• W421912185 title "Efficient Sparse Clustering of High-Dimensional Non-spherical Gaussian Mixtures" @default.
• W421912185 cites W1518092332 @default.
• W421912185 cites W1574816920 @default.
• W421912185 cites W1604976407 @default.
• W421912185 cites W1766266014 @default.
• W421912185 cites W18426229 @default.
• W421912185 cites W1848654034 @default.
• W421912185 cites W2025729801 @default.
• W421912185 cites W2030361786 @default.
• W421912185 cites W2040313973 @default.
• W421912185 cites W2047109555 @default.
• W421912185 cites W2048178552 @default.
• W421912185 cites W2051605894 @default.
• W421912185 cites W2052793367 @default.
• W421912185 cites W2056243712 @default.
• W421912185 cites W2062817469 @default.
• W421912185 cites W2075711194 @default.
• W421912185 cites W2079234446 @default.
• W421912185 cites W2088756548 @default.
• W421912185 cites W2099322651 @default.
• W421912185 cites W2108435369 @default.
• W421912185 cites W2147830002 @default.
• W421912185 cites W2160539666 @default.
• W421912185 cites W2963903176 @default.
• W421912185 cites W305865050 @default.
• W421912185 cites W2605159659 @default.
• W421912185 hasPublicationYear "2015" @default.
• W421912185 type Work @default.
• W421912185 sameAs 421912185 @default.
• W421912185 citedByCount "3" @default.
• W421912185 countsByYear W4219121852015 @default.
• W421912185 countsByYear W4219121852020 @default.
• W421912185 crossrefType "proceedings-article" @default.
• W421912185 hasAuthorship W421912185A5062033062 @default.
• W421912185 hasAuthorship W421912185A5073607469 @default.
• W421912185 hasAuthorship W421912185A5077874981 @default.
• W421912185 hasConcept C114614502 @default.
• W421912185 hasConcept C121332964 @default.
• W421912185 hasConcept C149872217 @default.
• W421912185 hasConcept C153180895 @default.
• W421912185 hasConcept C154945302 @default.
• W421912185 hasConcept C163716315 @default.
• W421912185 hasConcept C164866538 @default.
• W421912185 hasConcept C177264268 @default.
• W421912185 hasConcept C184509293 @default.
• W421912185 hasConcept C199360897 @default.
• W421912185 hasConcept C2778445095 @default.
• W421912185 hasConcept C33676613 @default.
• W421912185 hasConcept C33704608 @default.
• W421912185 hasConcept C33923547 @default.
• W421912185 hasConcept C41008148 @default.
• W421912185 hasConcept C61224824 @default.
• W421912185 hasConcept C62520636 @default.
• W421912185 hasConcept C69738355 @default.
• W421912185 hasConcept C73555534 @default.
• W421912185 hasConcept C94641424 @default.
• W421912185 hasConceptScore W421912185C114614502 @default.
• W421912185 hasConceptScore W421912185C121332964 @default.
• W421912185 hasConceptScore W421912185C149872217 @default.
• W421912185 hasConceptScore W421912185C153180895 @default.
• W421912185 hasConceptScore W421912185C154945302 @default.
• W421912185 hasConceptScore W421912185C163716315 @default.
• W421912185 hasConceptScore W421912185C164866538 @default.
• W421912185 hasConceptScore W421912185C177264268 @default.
• W421912185 hasConceptScore W421912185C184509293 @default.
• W421912185 hasConceptScore W421912185C199360897 @default.
• W421912185 hasConceptScore W421912185C2778445095 @default.
• W421912185 hasConceptScore W421912185C33676613 @default.
• W421912185 hasConceptScore W421912185C33704608 @default.
• W421912185 hasConceptScore W421912185C33923547 @default.
• W421912185 hasConceptScore W421912185C41008148 @default.
• W421912185 hasConceptScore W421912185C61224824 @default.
• W421912185 hasConceptScore W421912185C62520636 @default.
• W421912185 hasConceptScore W421912185C69738355 @default.
• W421912185 hasConceptScore W421912185C73555534 @default.
• W421912185 hasConceptScore W421912185C94641424 @default.
• W421912185 hasLocation W4219121851 @default.
• W421912185 hasOpenAccess W421912185 @default.
• W421912185 hasPrimaryLocation W4219121851 @default.
• W421912185 hasRelatedWork W1889586127 @default.
• W421912185 hasRelatedWork W2077326626 @default.
• W421912185 hasRelatedWork W2086846349 @default.
• W421912185 hasRelatedWork W2124935562 @default.
• W421912185 hasRelatedWork W2157063016 @default.
• W421912185 hasRelatedWork W2170204272 @default.
• W421912185 hasRelatedWork W2461263235 @default.
• W421912185 hasRelatedWork W2509988436 @default.
• W421912185 hasRelatedWork W2611846802 @default.
• W421912185 hasRelatedWork W2794886854 @default.
• W421912185 hasRelatedWork W2795744953 @default.
• W421912185 hasRelatedWork W2803475843 @default.

• next