Non-expansive hashing

Nathan Linial; Ori Sasson

doi:10.1007/PL00009805

Non-expansive hashing

Nathan Linial^*
, Ori Sasson

^*Corresponding author for this work

The Rachel and Selim Benin School of Engineering and Computer Science

Research output: Contribution to journal › Article › peer-review

3 Scopus citations

Abstract

In a non-expansive hashing scheme, similar inputs are stored in memory locations which are close. We develop a non-expansive hashing scheme wherein any set of size O(R^1-ε) from a large universe may be stored in a memory of size R (any ε > 0, and R > R₀(ε)), and where retrieval takes O(1) operations. We explain how to use non-expansive hashing schemes for efficient storage and retrieval of noisy data. A dynamic version of this hashing scheme is presented as well.

Original language	English
Pages (from-to)	121-132
Number of pages	12
Journal	Combinatorica
Volume	18
Issue number	1
DOIs	https://doi.org/10.1007/PL00009805
State	Published - 1998

Access to Document

10.1007/PL00009805

Cite this

@article{d082941c46b045ea8a3773763e8af303,

title = "Non-expansive hashing",

abstract = "In a non-expansive hashing scheme, similar inputs are stored in memory locations which are close. We develop a non-expansive hashing scheme wherein any set of size O(R1-ε) from a large universe may be stored in a memory of size R (any ε > 0, and R > R0(ε)), and where retrieval takes O(1) operations. We explain how to use non-expansive hashing schemes for efficient storage and retrieval of noisy data. A dynamic version of this hashing scheme is presented as well.",

author = "Nathan Linial and Ori Sasson",

year = "1998",

doi = "10.1007/PL00009805",

language = "אנגלית",

volume = "18",

pages = "121--132",

journal = "Combinatorica",

issn = "0209-9683",

publisher = "Janos Bolyai Mathematical Society",

number = "1",

}

TY - JOUR

T1 - Non-expansive hashing

AU - Linial, Nathan

AU - Sasson, Ori

PY - 1998

Y1 - 1998

N2 - In a non-expansive hashing scheme, similar inputs are stored in memory locations which are close. We develop a non-expansive hashing scheme wherein any set of size O(R1-ε) from a large universe may be stored in a memory of size R (any ε > 0, and R > R0(ε)), and where retrieval takes O(1) operations. We explain how to use non-expansive hashing schemes for efficient storage and retrieval of noisy data. A dynamic version of this hashing scheme is presented as well.

AB - In a non-expansive hashing scheme, similar inputs are stored in memory locations which are close. We develop a non-expansive hashing scheme wherein any set of size O(R1-ε) from a large universe may be stored in a memory of size R (any ε > 0, and R > R0(ε)), and where retrieval takes O(1) operations. We explain how to use non-expansive hashing schemes for efficient storage and retrieval of noisy data. A dynamic version of this hashing scheme is presented as well.

UR - https://www.scopus.com/pages/publications/0032410192

U2 - 10.1007/PL00009805

DO - 10.1007/PL00009805

M3 - ???researchoutput.researchoutputtypes.contributiontojournal.article???

AN - SCOPUS:0032410192

SN - 0209-9683

VL - 18

SP - 121

EP - 132

JO - Combinatorica

JF - Combinatorica

IS - 1

ER -

Non-expansive hashing

Abstract

Access to Document

Other files and links

Fingerprint

Cite this