What is the time complexity of matrix multiplication of sparse integer matrices with m in
nonzeros in the input and m out nonzeros in the output? This paper provides improved …

To respond to the need for efficient training and inference of deep neural networks, a
plethora of domain-specific architectures have been introduced, such as Google Tensor …

An Introduction to the Computational Complexity of Matrix Multiplication | SpringerLink Skip
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Abstract A tight\varOmega ((n/M)^\log _2 7 M) lower bound is derived on the I/O complexity
of Strassen's algorithm to multiply two n * n matrices, in a two-level storage hierarchy with M …

Motivated by studying the power of randomness, certifying algorithms and barriers for fine-
grained reductions, we investigate the question whether the multiplication of two $ n\times n …

To respond to the intense computational load of deep neural networks, a plethora of domain-
specific architectures have been introduced, such as Google Tensor Processing Units and …

Join evaluation is one of the most fundamental operations performed by database systems
and arguably the most well-studied problem in the Database community. A staggering …

Asymptotically tight lower bounds are derived for the I/O complexity of a general class of
hybrid algorithms computing the product of $ n\times n $ square matrices combining``\emph …

We study the problem of sparse matrix multiplication in the Random Access Machine and in
the Ideal Cache-Oblivious model. We present a simple algorithm that exploits randomization …

A basic question on two pieces of data is:“What is the similarity of the data?” In this extended
abstract we give an overview of new developments in randomized algorithms and data …