In this paper, we propose two new algorithms for maximum-likelihood estimation (MLE) of high dimensional sparse covariance matrices. Unlike most of the state-of-the-art methods, which either use ...

Sparse LU factorization is one of the key building blocks of sparse direct solvers and often dominates the computing time of circuit simulation programs. Existing GPU-accelerated sparse LU ...

Dr. James McCaffrey from Microsoft Research presents a complete end-to-end demonstration of computing a matrix inverse using the Cayley-Hamilton technique. Compared to other matrix inverse algorithms, ...

While the US is still far ahead in AI chip technology, China is following very closely in algorithms, says computer scientist Harry Shum.

Artificial Intelligence News. Everything on AI including futuristic robots with artificial intelligence, computer models of human intelligence and more.

Persistence of Vision - Ray Tracer. Philip Torr's stereo vision code - routines to generate synthetic data for testing and evaluating fundamental matrix estimation algorithms (by Philip Torr / Machine ...

The official SuiteSparse library: a suite of sparse matrix algorithms authored or co-authored by Tim Davis, Texas A&M University.

About Code accompanying the paper M. Sorel, F. Sroubek, "Fast convolutional sparse coding using matrix inversion lemma", Digital Signal Processing, vol. 55, pp.44-51, 2016 ...