As AI automates more knowledge work, the organizations that thrive will be those that master human relationships. Matrix organizations present well-known challenges: difficulty influencing across ...

AlphaEvolve uses large language models to find new algorithms that outperform the best human-made solutions for data center management, chip design, and more. Google DeepMind has once again used large ...

In this paper, the notion of equitable partitions (EP) is used to study the eigenvalues of Euclidean distance matrices (EDMs). In particular, EP is used to obtain the characteristic polynomials of ...

I propose the development of a new feature within our software framework: the implementation of the Locally Optimal Block Preconditioned Conjugate Gradient (LOBPCG) algorithm as a general eigenvalue ...

A matrix is a rectangular array of numbers, symbols, or expressions arranged in rows and columns. They are a crucial part of linear algebra and have various applications in fields like engineering, ...

Abstract: Solving the eigenvalues of matrices is an open problem which is often related to scientific computation. With the increasing of the order of matrices, traditional sequential algorithms are ...

Luckily, adjoint methods for (most) eigenvalue problems tend to be rather trivial if you are optimizing the eigenvalue directly. So, for example, if you want to match the effective index of two modes ...