2 Search Results for "Razenshteyn, Ilya"


Document
Tight Lower Bounds for Data-Dependent Locality-Sensitive Hashing

Authors: Alexandr Andoni and Ilya Razensteyn

Published in: LIPIcs, Volume 51, 32nd International Symposium on Computational Geometry (SoCG 2016)


Abstract
We prove a tight lower bound for the exponent rho for data-dependent Locality-Sensitive Hashing schemes, recently used to design efficient solutions for the c-approximate nearest neighbor search. In particular, our lower bound matches the bound of rho<= 1/(2c-1)+o(1) for the l_1 space, obtained via the recent algorithm from [Andoni-Razenshteyn, STOC'15]. In recent years it emerged that data-dependent hashing is strictly superior to the classical Locality-Sensitive Hashing, when the hash function is data-independent. In the latter setting, the best exponent has been already known: for the l_1 space, the tight bound is rho=1/c, with the upper bound from [Indyk-Motwani,STOC'98] and the matching lower bound from [O'Donnell-Wu-Zhou,ITCS'11]. We prove that, even if the hashing is data-dependent, it must hold that rho>=1/(2c-1)-o(1). To prove the result, we need to formalize the exact notion of data-dependent hashing that also captures the complexity of the hash functions (in addition to their collision properties). Without restricting such complexity, we would allow for obviously infeasible solutions such as the Voronoi diagram of a dataset. To preclude such solutions, we require our hash functions to be succinct. This condition is satisfied by all the known algorithmic results.

Cite as

Alexandr Andoni and Ilya Razensteyn. Tight Lower Bounds for Data-Dependent Locality-Sensitive Hashing. In 32nd International Symposium on Computational Geometry (SoCG 2016). Leibniz International Proceedings in Informatics (LIPIcs), Volume 51, pp. 9:1-9:11, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2016)


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@InProceedings{andoni_et_al:LIPIcs.SoCG.2016.9,
  author =	{Andoni, Alexandr and Razensteyn, Ilya},
  title =	{{Tight Lower Bounds for Data-Dependent Locality-Sensitive Hashing}},
  booktitle =	{32nd International Symposium on Computational Geometry (SoCG 2016)},
  pages =	{9:1--9:11},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-009-5},
  ISSN =	{1868-8969},
  year =	{2016},
  volume =	{51},
  editor =	{Fekete, S\'{a}ndor and Lubiw, Anna},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.SoCG.2016.9},
  URN =		{urn:nbn:de:0030-drops-59014},
  doi =		{10.4230/LIPIcs.SoCG.2016.9},
  annote =	{Keywords: similarity search, high-dimensional geometry, LSH, data structures, lower bounds}
}
Document
Restricted Isometry Property for General p-Norms

Authors: Zeyuan Allen-Zhu, Rati Gelashvili, and Ilya Razenshteyn

Published in: LIPIcs, Volume 34, 31st International Symposium on Computational Geometry (SoCG 2015)


Abstract
The Restricted Isometry Property (RIP) is a fundamental property of a matrix which enables sparse recovery. Informally, an m x n matrix satisfies RIP of order k for the L_p norm, if |Ax|_p is approximately |x|_p for every x with at most k non-zero coordinates. For every 1 <= p < infty we obtain almost tight bounds on the minimum number of rows m necessary for the RIP property to hold. Prior to this work, only the cases p = 1, 1 + 1/log(k), and 2 were studied. Interestingly, our results show that the case p=2 is a "singularity" point: the optimal number of rows m is Theta(k^p) for all p in [1, infty)-{2}, as opposed to Theta(k) for k=2. We also obtain almost tight bounds for the column sparsity of RIP matrices and discuss implications of our results for the Stable Sparse Recovery problem.

Cite as

Zeyuan Allen-Zhu, Rati Gelashvili, and Ilya Razenshteyn. Restricted Isometry Property for General p-Norms. In 31st International Symposium on Computational Geometry (SoCG 2015). Leibniz International Proceedings in Informatics (LIPIcs), Volume 34, pp. 451-460, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2015)


Copy BibTex To Clipboard

@InProceedings{allenzhu_et_al:LIPIcs.SOCG.2015.451,
  author =	{Allen-Zhu, Zeyuan and Gelashvili, Rati and Razenshteyn, Ilya},
  title =	{{Restricted Isometry Property for General p-Norms}},
  booktitle =	{31st International Symposium on Computational Geometry (SoCG 2015)},
  pages =	{451--460},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-939897-83-5},
  ISSN =	{1868-8969},
  year =	{2015},
  volume =	{34},
  editor =	{Arge, Lars and Pach, J\'{a}nos},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.SOCG.2015.451},
  URN =		{urn:nbn:de:0030-drops-51273},
  doi =		{10.4230/LIPIcs.SOCG.2015.451},
  annote =	{Keywords: compressive sensing, dimension reduction, linear algebra, high-dimensional geometry}
}
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