Recent research has explored various aspects of complexity theory, including connections between graph theory and matrix spaces, the computation of determinants, and optimization problems.

Can artificial intelligence (AI) create its own algorithms to speed up matrix multiplication, one of machine learning’s most fundamental tasks? Today, in a paper published in Nature, DeepMind ...

In this video, we delve into the fascinating world of big number multiplication and explore how computers perform this task ...

What do encrypted messages, recognizing speech commands and running simulations to predict the weather have in common? They all rely on matrix multiplication for accurate calculations. DeepMind, an ...

It is well known that their approach can also be used to solve the general problem, without affecting the complexity of the algorithm. In this paper, we present an algorithm to solve the economic lot ...

Indeed, to date, no practical algorithm for estimating the permanent of a matrix has been devised. It is an open question whether such an algorithm exists. Another open question is whether there is a ...

A simple matrix formula is given for the observed information matrix when the EM algorithm is applied to categorical data with missing values. The formula requires only the design matrices, a matrix ...

Complexity Theory and Polynomial Time Algorithms Publication Trend The graph below shows the total number of publications each year in Complexity Theory and Polynomial Time Algorithms.