AbstractThe paper is a systematic survey of recently developed methods for the acceleration of MM, matrix multiplication, with some attention to the connections between MM and other computational problems (Boolean MM, Direct Sum Conjecture or DSC). The techniques of trilinear aggregating, uniting and canceling, AUC, due to the author, give the exponent < 2.77614 and a small constant defining an upper bounds on the both complexities, of MM and Boolean MM. By combining AUC with other recent techniques due to Bini, Capovani, Lotti, Romani, Schönhage and Winograd, the exponent was recently reduced to less than 2.5161 by the price of a serious increase of the constant. The AUC techniques are used to disprove DSC over the class of any precision a...
In this work, we prove limitations on the known methods for designing matrix multiplication algorith...
AbstractFirst we study asymptotically fast algorithms for rectangular matrix multiplication. We begi...
Matrix multiplication is commonly used in scientific computation. Given matrices A = (aij ) of size ...
AbstractThe paper is a systematic survey of recently developed methods for the acceleration of MM, m...
Matrix multiplication (hereafter we use the acronym MM) is among the most fundamental operations of ...
AbstractThe method of trilinear aggregating with implicit canceling for the design of fast matrix mu...
AbstractThe recent progress in the asymptotic acceleration of matrix multiplication and of related m...
AbstractWe present several bilinear algorithms for the acceleration of multiplication of n X n matri...
AbstractA new improvement of author's techniques of trilinear aggregating, uniting and canceling, is...
Matrix multiplication is a basic operation of linear algebra, and has numerous applications to the t...
AbstractThe main purpose of this paper is to present a fast matrix multiplication algorithm taken fr...
The complexity of matrix multiplication (hereafter MM) has been intensively studied since 1969, when...
The evaluation of the product of two matrices can be very computationally expensive. The multiplica...
AbstractThe complexity of matrix multiplication has attracted a lot of attention in the last forty y...
Matrix multiplication is a core building block for numerous scientific computing and, more recently,...
In this work, we prove limitations on the known methods for designing matrix multiplication algorith...
AbstractFirst we study asymptotically fast algorithms for rectangular matrix multiplication. We begi...
Matrix multiplication is commonly used in scientific computation. Given matrices A = (aij ) of size ...
AbstractThe paper is a systematic survey of recently developed methods for the acceleration of MM, m...
Matrix multiplication (hereafter we use the acronym MM) is among the most fundamental operations of ...
AbstractThe method of trilinear aggregating with implicit canceling for the design of fast matrix mu...
AbstractThe recent progress in the asymptotic acceleration of matrix multiplication and of related m...
AbstractWe present several bilinear algorithms for the acceleration of multiplication of n X n matri...
AbstractA new improvement of author's techniques of trilinear aggregating, uniting and canceling, is...
Matrix multiplication is a basic operation of linear algebra, and has numerous applications to the t...
AbstractThe main purpose of this paper is to present a fast matrix multiplication algorithm taken fr...
The complexity of matrix multiplication (hereafter MM) has been intensively studied since 1969, when...
The evaluation of the product of two matrices can be very computationally expensive. The multiplica...
AbstractThe complexity of matrix multiplication has attracted a lot of attention in the last forty y...
Matrix multiplication is a core building block for numerous scientific computing and, more recently,...
In this work, we prove limitations on the known methods for designing matrix multiplication algorith...
AbstractFirst we study asymptotically fast algorithms for rectangular matrix multiplication. We begi...
Matrix multiplication is commonly used in scientific computation. Given matrices A = (aij ) of size ...