Deterministic algorithms for skewed matrix products

Konstantin Kutzkov

doi:10.4230/LIPIcs.STACS.2013.466

Deterministic algorithms for skewed matrix products

Konstantin Kutzkov

Publikation: Artikel i tidsskrift og konference artikel i tidsskrift › Tidsskriftartikel › Forskning › peer review

Abstract

Recently, Pagh presented a randomized approximation algorithm for the multiplication of
real-valued matrices building upon work for detecting the most frequent items in data streams.
We continue this line of research and present new deterministic matrix multiplication algorithms.

Originalsprog	Engelsk
Tidsskrift	Dagstuhl Seminar Proceedings
Antal sider	12
ISSN	1862-4405
DOI	https://doi.org/10.4230/LIPIcs.STACS.2013.466
Status	Udgivet - 2013

Emneord

approximate deterministic memory-efficient matrix multiplication

Adgang til dokumentet

10.4230/LIPIcs.STACS.2013.466

http://www.itu.dk/people/konk/papers/dmm_stacs.pdf

MaDaMS: Massive Data Mining by Sampling
Pagh, R. (PI), Stöckel, M. (CoI) & Pham, N. D. (CoI)
Danmarks Frie Forskningsfond
01/01/2011 → 31/12/2014
Projekter: Projekt › Forskning

Citationsformater

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keywords = "approximate deterministic memory-efficient matrix multiplication, approximate deterministic memory-efficient matrix multiplication",

author = "Konstantin Kutzkov",

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year = "2013",

doi = "10.4230/LIPIcs.STACS.2013.466",

language = "English",

journal = "Dagstuhl Seminar Proceedings",

issn = "1862-4405",

publisher = "Schloss Dagstuhl - Leibniz-Zentrum fuer Informatik GmbH",

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TY - JOUR

T1 - Deterministic algorithms for skewed matrix products

AU - Kutzkov, Konstantin

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PY - 2013

Y1 - 2013

N2 - Recently, Pagh presented a randomized approximation algorithm for the multiplication ofreal-valued matrices building upon work for detecting the most frequent items in data streams.We continue this line of research and present new deterministic matrix multiplication algorithms.

AB - Recently, Pagh presented a randomized approximation algorithm for the multiplication ofreal-valued matrices building upon work for detecting the most frequent items in data streams.We continue this line of research and present new deterministic matrix multiplication algorithms.

KW - approximate deterministic memory-efficient matrix multiplication

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DO - 10.4230/LIPIcs.STACS.2013.466

M3 - Journal article

SN - 1862-4405

JO - Dagstuhl Seminar Proceedings

JF - Dagstuhl Seminar Proceedings

ER -

Deterministic algorithms for skewed matrix products

Abstract

Emneord

Adgang til dokumentet

Fingeraftryk

Projekter

MaDaMS: Massive Data Mining by Sampling

Citationsformater