科学技術振興機構

[Hideyuki Ishi] Innovative technologies in mathematical science about positive definite symmetric matrices

Symmetric matrices of huge size with many zero entries, called sparse symmetric matrices, are nowadays studied actively in the context of artificial intelligence and data science. One of the efficient ...
JSTOR Daily

On Rank Estimation in Symmetric Matrices: The Case of Indefinite Matrix Estimators

This is a preview. Log in through your library . Abstract In this paper we consider estimating the rank of an unknown symmetric matrix based on a symmetric, asymptotically normal estimator of the ...
IEEE

A Hebbian/Anti-Hebbian network for online sparse dictionary learning derived from symmetric matrix factorization

Abstract: Olshausen and Field (OF) proposed that neural computations in the primary visual cortex (V1) can be partially modelled by sparse dictionary learning. By ...
JSTOR Daily

A Decomposition of an Idempotent Matrix Where Nonnegativity Implies Idempotence and None of the Matrices Need Be Symmetric

Sankhyā: The Indian Journal of Statistics, Series A (1961-2002), Vol. 38, No. 4 (Oct., 1976), pp. 400-403 (4 pages) A theorem involving the decomposition of an idempotent matrix into the sum of one or ...