Deterministic Length Reduction: Fast Convolution in Sparse Data

A. Amihood; Oren Kapah; E. Porat

Deterministic Length Reduction: Fast Convolution in Sparse Data

A. Amihood, Oren Kapah, E. Porat

Department of Computer Science

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

In this paper a deterministic algorithm for the length reduction problem is presented. This algorithm enables a new tool for performing fast convolution in sparse data. The proposed algorithm performs the convolution in O(n1log3n1)O(n1log3⁡n1), where n 1 is the number of non-zero values in V 1. This algorithm assumes that V 1 is given in advance, and the V 2 is given in running time.

Original language	American English
Title of host publication	Annual Symposium on Combinatorial Pattern Matching
Editors	Bin Ma, Kaizhong Zhang
Publisher	Springer Berlin Heidelberg
State	Published - 2007

Bibliographical note

Place of conference:London, Canada

Cite this

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title = "Deterministic Length Reduction: Fast Convolution in Sparse Data",

abstract = "In this paper a deterministic algorithm for the length reduction problem is presented. This algorithm enables a new tool for performing fast convolution in sparse data. The proposed algorithm performs the convolution in O(n1log3n1)O(n1log3⁡n1), where n 1 is the number of non-zero values in V 1. This algorithm assumes that V 1 is given in advance, and the V 2 is given in running time.",

author = "A. Amihood and Oren Kapah and E. Porat",

note = "Place of conference:London, Canada",

year = "2007",

language = "American English",

editor = "Bin Ma and Kaizhong Zhang",

booktitle = "Annual Symposium on Combinatorial Pattern Matching",

publisher = "Springer Berlin Heidelberg",

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T1 - Deterministic Length Reduction: Fast Convolution in Sparse Data

AU - Amihood, A.

AU - Kapah, Oren

AU - Porat, E.

N1 - Place of conference:London, Canada

PY - 2007

Y1 - 2007

N2 - In this paper a deterministic algorithm for the length reduction problem is presented. This algorithm enables a new tool for performing fast convolution in sparse data. The proposed algorithm performs the convolution in O(n1log3n1)O(n1log3⁡n1), where n 1 is the number of non-zero values in V 1. This algorithm assumes that V 1 is given in advance, and the V 2 is given in running time.

AB - In this paper a deterministic algorithm for the length reduction problem is presented. This algorithm enables a new tool for performing fast convolution in sparse data. The proposed algorithm performs the convolution in O(n1log3n1)O(n1log3⁡n1), where n 1 is the number of non-zero values in V 1. This algorithm assumes that V 1 is given in advance, and the V 2 is given in running time.

UR - https://scholar.google.co.il/scholar?q=Deterministic+Length+Reduction%3A+Fast+Convolution+in+Sparse+Data%2C+Amir+Amihood+&btnG=&hl=en&as_sdt=0%2C5

M3 - Conference contribution

BT - Annual Symposium on Combinatorial Pattern Matching

A2 - Ma, Bin

A2 - Zhang, Kaizhong

PB - Springer Berlin Heidelberg

ER -

Deterministic Length Reduction: Fast Convolution in Sparse Data

Abstract

Bibliographical note

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