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  • 标题:Simple Analyses of the Sparse Johnson-Lindenstrauss Transform
  • 本地全文:下载
  • 作者:Michael B. Cohen ; T.S. Jayram ; Jelani Nelson
  • 期刊名称:OASIcs : OpenAccess Series in Informatics
  • 电子版ISSN:2190-6807
  • 出版年度:2018
  • 卷号:61
  • 页码:15:1-15:9
  • DOI:10.4230/OASIcs.SOSA.2018.15
  • 出版社:Schloss Dagstuhl -- Leibniz-Zentrum fuer Informatik
  • 摘要:For every n-point subset X of Euclidean space and target distortion 1+eps for 0l_2^m where f(x) = Ax for A a matrix with m rows where (1) m = O((log n)/eps^2), and (2) each column of A is sparse, having only O(eps m) non-zero entries. Though the constructions given for such A in (Kane, Nelson, J. ACM 2014) are simple, the analyses are not, employing intricate combinatorial arguments. We here give two simple alternative proofs of their main result, involving no delicate combinatorics. One of these proofs has already been tested pedagogically, requiring slightly under forty minutes by the third author at a casual pace to cover all details in a blackboard course lecture.
  • 关键词:dimensionality reduction; Johnson-Lindenstrauss; Sparse Johnson-Lindenstrauss Transform
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