rolv LLC Launches rolvsparse(c): A New Mathematical Operator That Makes Every Computer on Earth Run AI Faster -- With 99% Less Energy

University of Miami Frost Institute independently confirms 50× speedups and 90--99.9% energy savings across CPUs, GPUs, TPUs, and AI accelerators -- identical SHA-256 verified results on all platforms ...
GitHub

Ultra‑Sparse Matrix Factorization Recommender System

This repository explores how well a Biased Latent Matrix Factorization (BLMF) recommender system performs when trained on extremely sparse rating matrices, using a reduced sample of the MovieLens 32M ...
Frontiers

Interleaving cortex-analog mixing improves deep non-negative matrix factorization networks

Considering biological constraints in artificial neural networks has led to dramatic improvements in performance. Nevertheless, to date, the positivity of long-range signals in the cortex has not been ...
Scientific Research Publishing

Koren, Y., Bell, R., & Volinsky, C. (2009). Matrix Factorization Techniques for Recommender Systems. Computer, 42, 30-37.

ABSTRACT: The offline course “Home Plant Health Care,” which is available to the senior population, serves as the study object for this paper. Learn how to use artificial intelligence technologies to ...
Nature

Sparse matrix factorization robust to sample sharing across GWASs reveals interpretable genetic components

The Nature Index 2025 Research Leaders — previously known as Annual Tables — reveal the leading institutions and countries/territories in the natural and health sciences, according to their output in ...
IEEE

An Innovative Low-Rank Sparse Matrix Decomposition Clutter Suppression Method Based on Non-Convex Alternatives for Pseudo-Random-Coded Ground-Penetrating Radar

Abstract: This article analyzes the composition and characteristics of echo signals in a pseudorandom-coded ground-penetrating radar (GPR). Based on these characteristics, an innovative low-rank ...
Scientific Research Publishing

Gibbs, N.E., Poole, Jr., W.G. and Stockmeyer, P.K. (1976) An Algorithm for Reducing the Bandwidth and Profile of a Sparse Matrix. SIAM Journal on Numerical Analysis, 13, 236-250.

ABSTRACT: Node renumbering is an important step in the solution of sparse systems of equations. It aims to reduce the bandwidth and profile of the matrix. This allows for the speeding up of the ...
GitHub

sparse-matrix-vector-multiplication

Hand-tuned WebAssembly implementations for efficient execution of web-based sparse computations including Sparse Matrix-Vector Multiplication (SpMV), sparse triangular solve (SpTS) and other useful ...