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  • 标题:Simple Average-Case Lower Bounds for Approximate Near-Neighbor from Isoperimetric Inequalities
  • 本地全文:下载
  • 作者:Yitong Yin
  • 期刊名称:LIPIcs : Leibniz International Proceedings in Informatics
  • 电子版ISSN:1868-8969
  • 出版年度:2016
  • 卷号:55
  • 页码:84:1-84:13
  • DOI:10.4230/LIPIcs.ICALP.2016.84
  • 出版社:Schloss Dagstuhl -- Leibniz-Zentrum fuer Informatik
  • 摘要:We prove an Omega(d/log(sw/nd)) lower bound for the average-case cell-probe complexity of deterministic or Las Vegas randomized algorithms solving approximate near-neighbor (ANN) problem in ddimensional Hamming space in the cell-probe model with w-bit cells, using a table of size s. This lower bound matches the highest known worst-case cell-probe lower bounds for any static data structure problems. This average-case cell-probe lower bound is proved in a general framework which relates the cell-probe complexity of ANN to isoperimetric inequalities in the underlying metric space. A tighter connection between ANN lower bounds and isoperimetric inequalities is established by a stronger richness lemma proved by cell-sampling techniques.
  • 关键词:nearest neighbor search; approximate near-neighbor; cell-probe model; isoperimetric inequality
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