What can you do about data sparsity? What do you do when you have a matrix with a bunch of zeros in it, and you can't get a good look at a complex system because so many of the nodes are empty? Matrix ...

Sparse data can impact the effectiveness of machine learning models. As students and experts alike experiment with diverse datasets, sparse data poses a challenge. The Leeds Master’s in Business ...

High sparse Knowledge Graph is a key challenge to solve the Knowledge Graph Completion task. Due to the sparsity of the KGs, there are not enough first-order neighbors to learn the features of ...

Regularization of covariance matrices in high dimensions usually either is based on a known ordering of variables or ignores the ordering entirely. This article proposes a method for discovering ...

Suppose you have a thousand-page book, but each page has only a single line of text. You’re supposed to extract the information contained in the book using a scanner, only this particular scanner ...

How do you measure the performance of the world’s biggest supercomputers? Developed at Sandia National Laboratories, the HPCG benchmark is intended as a complement to the High Performance LINPACK (HPL ...

I'm getting ready to start working on a C/C++ project that will be building and solving large tri-diagonal, block tri-diagonal and triangular matrices. I know there are a lot of libraries available ...