Performing math on multidimensional arrays very efficiently. For example, the Strassen algorithm uses fast matrix math on large matrices. See multidimensional array. THIS DEFINITION IS FOR PERSONAL ...

Want smarter insights in your inbox? Sign up for our weekly newsletters to get only what matters to enterprise AI, data, and security leaders. Subscribe Now Today, D-Matrix, a company focused on ...

M.Sc. in Applied Mathematics, Technion (Israel Institute of Technology) Ph.D. in Applied Mathematics, Caltech (California Institute of Technology) [1] A. Melman (2023): “Matrices whose eigenvalues are ...

Over the last few years the idea of “conditional computation” has been key to making neural network processing more efficient, even though much of the hardware ecosystem has focused on general purpose ...

We present a test for determining if a substochastic matrix is convergent. By establishing a duality between weakly chained diagonally dominant (w.c.d.d.) L-matrices and convergent substochastic ...

Want smarter insights in your inbox? Sign up for our weekly newsletters to get only what matters to enterprise AI, data, and security leaders. Subscribe Now Can artificial intelligence (AI) create its ...

For a completely general partitioned matrix of the form $M = \begin{bmatrix}A & C\\R & D\end{bmatrix},$ a representation for (1)- and (1,2)-inverses of M is derived ...

Current custom AI hardware devices are built around super-efficient, high performance matrix multiplication. This category of accelerators includes the host of AI chip startups and defines what more ...