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zbMATH Open
Article . 1981
Data sources: zbMATH Open
SIAM Journal on Computing
Article . 1981 . Peer-reviewed
Data sources: Crossref
DBLP
Article . 2017
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Partial and Total Matrix Multiplication

Partial and total matrix multiplication
Authors: Arnold Schönhage;

Partial and Total Matrix Multiplication

Abstract

In 1979 considerable progress was made in estimating the complexity of matrix multiplication. Here the new techniques and recent results are presented, based upon the notion of approximate rank and the observation that certain patterns of partial matrix multiplication (some of the entries of the matrices may be zero) can efficiently be utilized to perform multiplication of large total matrices. By combining Pan’s trilinear technique with a strong version of our compression theorem for the case of several disjoint matrix multiplications it is shown that multiplication of $N \times N$ matrices (over arbitrary fields) is possible in time $O(N^\beta )$, where $\beta $ is a bit smaller than $3\ln 52/\ln 110 \approx 2.522$.

Keywords

compression theorem, Analysis of algorithms and problem complexity, Other matrix algorithms, tensor rank, trilinear aggregating

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
143
Top 1%
Top 0.1%
Top 10%
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