Matches in SemOpenAlex for { <https://semopenalex.org/work/W1618327071> ?p ?o ?g. }
Showing items 1 to 93 of
93
with 100 items per page.
- W1618327071 endingPage "338" @default.
- W1618327071 startingPage "328" @default.
- W1618327071 abstract "Analyzing massive data sets has been one of the key motivations for studying streaming algorithms. In recent years, there has been significant progress in analysing distributions in a streaming setting, but the progress on graph problems has been limited. A main reason for this has been the existence of linear space lower bounds for even simple problems such as determining the connectedness of a graph. However, in many new scenarios that arise from social and other interaction networks, the number of vertices is significantly less than the number of edges. This has led to the formulation of the semi-streaming model where we assume that the space is (near) linear in the number of vertices (but not necessarily the edges), and the edges appear in an arbitrary (and possibly adversarial) order. However there has been limited progress in analysing graph algorithms in this model. In this paper we focus on graph sparsification, which is one of the major building blocks in a variety of graph algorithms. Further, there has been a long history of (non-streaming) sampling algorithms that provide sparse graph approximations and it a natural question to ask: since the end result of the sparse approximation is a small (linear) space structure, can we achieve that using a small space, and in addition using a single pass over the data? The question is interesting from the standpoint of both theory and practice and we answer the question in the affirmative, by providing a one pass $tilde{O}(n/epsilon^{2})$ space algorithm that produces a sparsification that approximates each cut to a (1 + ε) factor. We also show that $Omega(n log frac1epsilon)$ space is necessary for a one pass streaming algorithm to approximate the min-cut, improving upon the Ω(n) lower bound that arises from lower bounds for testing connectivity." @default.
- W1618327071 created "2016-06-24" @default.
- W1618327071 creator A5017534381 @default.
- W1618327071 creator A5068326243 @default.
- W1618327071 date "2009-01-01" @default.
- W1618327071 modified "2023-10-05" @default.
- W1618327071 title "Graph Sparsification in the Semi-streaming Model" @default.
- W1618327071 cites W1514707655 @default.
- W1618327071 cites W1761167196 @default.
- W1618327071 cites W1964510837 @default.
- W1618327071 cites W1965972569 @default.
- W1618327071 cites W1983266860 @default.
- W1618327071 cites W2042587503 @default.
- W1618327071 cites W2051540665 @default.
- W1618327071 cites W2068888615 @default.
- W1618327071 cites W2080745194 @default.
- W1618327071 cites W2115049345 @default.
- W1618327071 cites W2165753192 @default.
- W1618327071 cites W2168919539 @default.
- W1618327071 cites W4245136207 @default.
- W1618327071 doi "https://doi.org/10.1007/978-3-642-02930-1_27" @default.
- W1618327071 hasPublicationYear "2009" @default.
- W1618327071 type Work @default.
- W1618327071 sameAs 1618327071 @default.
- W1618327071 citedByCount "53" @default.
- W1618327071 countsByYear W16183270712012 @default.
- W1618327071 countsByYear W16183270712013 @default.
- W1618327071 countsByYear W16183270712014 @default.
- W1618327071 countsByYear W16183270712015 @default.
- W1618327071 countsByYear W16183270712016 @default.
- W1618327071 countsByYear W16183270712017 @default.
- W1618327071 countsByYear W16183270712018 @default.
- W1618327071 countsByYear W16183270712019 @default.
- W1618327071 countsByYear W16183270712020 @default.
- W1618327071 countsByYear W16183270712021 @default.
- W1618327071 countsByYear W16183270712022 @default.
- W1618327071 countsByYear W16183270712023 @default.
- W1618327071 crossrefType "book-chapter" @default.
- W1618327071 hasAuthorship W1618327071A5017534381 @default.
- W1618327071 hasAuthorship W1618327071A5068326243 @default.
- W1618327071 hasBestOaLocation W16183270712 @default.
- W1618327071 hasConcept C11413529 @default.
- W1618327071 hasConcept C118615104 @default.
- W1618327071 hasConcept C13251829 @default.
- W1618327071 hasConcept C132525143 @default.
- W1618327071 hasConcept C134306372 @default.
- W1618327071 hasConcept C15744967 @default.
- W1618327071 hasConcept C187166803 @default.
- W1618327071 hasConcept C201943243 @default.
- W1618327071 hasConcept C203776342 @default.
- W1618327071 hasConcept C33923547 @default.
- W1618327071 hasConcept C41008148 @default.
- W1618327071 hasConcept C43517604 @default.
- W1618327071 hasConcept C542102704 @default.
- W1618327071 hasConcept C77553402 @default.
- W1618327071 hasConcept C80444323 @default.
- W1618327071 hasConceptScore W1618327071C11413529 @default.
- W1618327071 hasConceptScore W1618327071C118615104 @default.
- W1618327071 hasConceptScore W1618327071C13251829 @default.
- W1618327071 hasConceptScore W1618327071C132525143 @default.
- W1618327071 hasConceptScore W1618327071C134306372 @default.
- W1618327071 hasConceptScore W1618327071C15744967 @default.
- W1618327071 hasConceptScore W1618327071C187166803 @default.
- W1618327071 hasConceptScore W1618327071C201943243 @default.
- W1618327071 hasConceptScore W1618327071C203776342 @default.
- W1618327071 hasConceptScore W1618327071C33923547 @default.
- W1618327071 hasConceptScore W1618327071C41008148 @default.
- W1618327071 hasConceptScore W1618327071C43517604 @default.
- W1618327071 hasConceptScore W1618327071C542102704 @default.
- W1618327071 hasConceptScore W1618327071C77553402 @default.
- W1618327071 hasConceptScore W1618327071C80444323 @default.
- W1618327071 hasLocation W16183270711 @default.
- W1618327071 hasLocation W16183270712 @default.
- W1618327071 hasLocation W16183270713 @default.
- W1618327071 hasLocation W16183270714 @default.
- W1618327071 hasOpenAccess W1618327071 @default.
- W1618327071 hasPrimaryLocation W16183270711 @default.
- W1618327071 hasRelatedWork W2023497185 @default.
- W1618327071 hasRelatedWork W2381880241 @default.
- W1618327071 hasRelatedWork W2386767533 @default.
- W1618327071 hasRelatedWork W2391817034 @default.
- W1618327071 hasRelatedWork W2929414291 @default.
- W1618327071 hasRelatedWork W2951849116 @default.
- W1618327071 hasRelatedWork W2952096553 @default.
- W1618327071 hasRelatedWork W3101796089 @default.
- W1618327071 hasRelatedWork W4301148595 @default.
- W1618327071 hasRelatedWork W4317655900 @default.
- W1618327071 isParatext "false" @default.
- W1618327071 isRetracted "false" @default.
- W1618327071 magId "1618327071" @default.
- W1618327071 workType "book-chapter" @default.