Matches in SemOpenAlex for { <https://semopenalex.org/work/W3103717559> ?p ?o ?g. }
Showing items 1 to 92 of
92
with 100 items per page.
- W3103717559 endingPage "1281" @default.
- W3103717559 startingPage "1281" @default.
- W3103717559 abstract "Stochastic separation theorems play important roles in high-dimensional data analysis and machine learning. It turns out that in high dimensional space, any point of a random set of points can be separated from other points by a hyperplane with high probability, even if the number of points is exponential in terms of dimensions. This and similar facts can be used for constructing correctors for artificial intelligent systems, for determining the intrinsic dimensionality of data and for explaining various natural intelligence phenomena. In this paper, we refine the estimations for the number of points and for the probability in stochastic separation theorems, thereby strengthening some results obtained earlier. We propose the boundaries for linear and Fisher separability, when the points are drawn randomly, independently and uniformly from a d-dimensional spherical layer and from the cube. These results allow us to better outline the applicability limits of the stochastic separation theorems in applications." @default.
- W3103717559 created "2020-11-23" @default.
- W3103717559 creator A5040424411 @default.
- W3103717559 creator A5091565051 @default.
- W3103717559 date "2020-11-12" @default.
- W3103717559 modified "2023-09-25" @default.
- W3103717559 title "Linear and Fisher Separability of Random Points in the d-Dimensional Spherical Layer and Inside the d-Dimensional Cube" @default.
- W3103717559 cites W1971216370 @default.
- W3103717559 cites W2027392196 @default.
- W3103717559 cites W2036568591 @default.
- W3103717559 cites W2144006746 @default.
- W3103717559 cites W2321124713 @default.
- W3103717559 cites W2593455419 @default.
- W3103717559 cites W2884716758 @default.
- W3103717559 cites W2892053535 @default.
- W3103717559 cites W2952773203 @default.
- W3103717559 cites W2978147885 @default.
- W3103717559 cites W2979001048 @default.
- W3103717559 cites W2999763174 @default.
- W3103717559 cites W3090177494 @default.
- W3103717559 cites W3099723194 @default.
- W3103717559 doi "https://doi.org/10.3390/e22111281" @default.
- W3103717559 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/7712262" @default.
- W3103717559 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/33287049" @default.
- W3103717559 hasPublicationYear "2020" @default.
- W3103717559 type Work @default.
- W3103717559 sameAs 3103717559 @default.
- W3103717559 citedByCount "2" @default.
- W3103717559 countsByYear W31037175592021 @default.
- W3103717559 crossrefType "journal-article" @default.
- W3103717559 hasAuthorship W3103717559A5040424411 @default.
- W3103717559 hasAuthorship W3103717559A5091565051 @default.
- W3103717559 hasBestOaLocation W31037175591 @default.
- W3103717559 hasConcept C105795698 @default.
- W3103717559 hasConcept C111030470 @default.
- W3103717559 hasConcept C11413529 @default.
- W3103717559 hasConcept C114614502 @default.
- W3103717559 hasConcept C134306372 @default.
- W3103717559 hasConcept C151376022 @default.
- W3103717559 hasConcept C177264268 @default.
- W3103717559 hasConcept C199360897 @default.
- W3103717559 hasConcept C21080849 @default.
- W3103717559 hasConcept C2524010 @default.
- W3103717559 hasConcept C28719098 @default.
- W3103717559 hasConcept C31243852 @default.
- W3103717559 hasConcept C33923547 @default.
- W3103717559 hasConcept C41008148 @default.
- W3103717559 hasConcept C53051483 @default.
- W3103717559 hasConcept C68693459 @default.
- W3103717559 hasConcept C8272713 @default.
- W3103717559 hasConcept C88871306 @default.
- W3103717559 hasConceptScore W3103717559C105795698 @default.
- W3103717559 hasConceptScore W3103717559C111030470 @default.
- W3103717559 hasConceptScore W3103717559C11413529 @default.
- W3103717559 hasConceptScore W3103717559C114614502 @default.
- W3103717559 hasConceptScore W3103717559C134306372 @default.
- W3103717559 hasConceptScore W3103717559C151376022 @default.
- W3103717559 hasConceptScore W3103717559C177264268 @default.
- W3103717559 hasConceptScore W3103717559C199360897 @default.
- W3103717559 hasConceptScore W3103717559C21080849 @default.
- W3103717559 hasConceptScore W3103717559C2524010 @default.
- W3103717559 hasConceptScore W3103717559C28719098 @default.
- W3103717559 hasConceptScore W3103717559C31243852 @default.
- W3103717559 hasConceptScore W3103717559C33923547 @default.
- W3103717559 hasConceptScore W3103717559C41008148 @default.
- W3103717559 hasConceptScore W3103717559C53051483 @default.
- W3103717559 hasConceptScore W3103717559C68693459 @default.
- W3103717559 hasConceptScore W3103717559C8272713 @default.
- W3103717559 hasConceptScore W3103717559C88871306 @default.
- W3103717559 hasIssue "11" @default.
- W3103717559 hasLocation W31037175591 @default.
- W3103717559 hasLocation W31037175592 @default.
- W3103717559 hasLocation W31037175593 @default.
- W3103717559 hasOpenAccess W3103717559 @default.
- W3103717559 hasPrimaryLocation W31037175591 @default.
- W3103717559 hasRelatedWork W2238117203 @default.
- W3103717559 hasRelatedWork W2527479668 @default.
- W3103717559 hasRelatedWork W2591746957 @default.
- W3103717559 hasRelatedWork W2679921595 @default.
- W3103717559 hasRelatedWork W2951554766 @default.
- W3103717559 hasRelatedWork W3007555197 @default.
- W3103717559 hasRelatedWork W3023514161 @default.
- W3103717559 hasRelatedWork W3103717559 @default.
- W3103717559 hasRelatedWork W4214576944 @default.
- W3103717559 hasRelatedWork W4302583305 @default.
- W3103717559 hasVolume "22" @default.
- W3103717559 isParatext "false" @default.
- W3103717559 isRetracted "false" @default.
- W3103717559 magId "3103717559" @default.
- W3103717559 workType "article" @default.