Structured low-rank approximation (SLRA) is a mathematical framework that seeks to approximate a given data matrix by another matrix of lower rank while preserving intrinsic structural properties.

S. W. Ellacott, Computation of Faber Series With Application to Numerical Polynomial Approximation in the Complex Plane, Mathematics of Computation, Vol. 40, No. 162 ...

HUIYUAN LI, JIE SHEN, OPTIMAL ERROR ESTIMATES IN JACOBI-WEIGHTED SOBOLEV SPACES FOR POLYNOMIAL APPROXIMATIONS ON THE TRIANGLE, Mathematics of Computation, Vol. 79, No. 271 (JULY 2010), pp. 1621-1646 ...

Matrix Functions and Their Approximations Publication Trend The graph below shows the total number of publications each year in Matrix Functions and Their Approximations.

First, they demonstrated an error-resistant implementation of universal quantum gates, the essential building blocks of quantum computation.

Quantum computers, systems that perform computations leveraging quantum mechanical effects, could outperform classical computers in some optimization and information processing tasks. As these systems ...

First, they demonstrated an error-resistant implementation of universal quantum gates, the essential building blocks of quantum computation.