Yes, and here’s how. Read on to learn how two commonly used algorithms – matrix factorization and a bipartite graph—can be used to deliver personalization in an application.

Xuefeng Liu, Michael J. Daniels, A New Algorithm for Simulating a Correlation Matrix Based on Parameter Expansion and Reparameterization, Journal of Computational and Graphical Statistics, Vol. 15, No ...

Matrix factorization algorithms help track neuronal activity They then excited the beads using blue laser light and collected the resulting fluorescence speckles using first a microscope objective and ...

Since this EM algorithm uses filtering and smoothing, you can learn how to use the KALCVF and KALCVS calls to analyze the data. Consider the bivariate SSM: where H is a 2 ×2 identity matrix, the ...

The other matrix represents the input data; for example, the pixels of an image to be classified. MADDNESS is based on a vector quantization algorithm called product quantization (PQ).

The DETMAX algorithm of Mitchell (1974a) is very commonly used for computer-generated optimal design. Although it is not the default search method for the OPTEX procedure, you can specify that it be ...

SIAM Journal on Numerical Analysis, Vol. 10, No. 2 (Apr., 1973), pp. 241-256 (16 pages) A new method, called the QZ algorithm, is presented for the solution of the matrix eigenvalue problem Ax = λ Bx ...

A new research paper titled “Discovering faster matrix multiplication algorithms with reinforcement learning” was published by researchers at DeepMind. “Here we report a deep reinforcement learning ...

vivo’s algorithm matrix solution vivo and ZEISS jointly announced a periscope lens design with the new “Vario-Apo-Sonnar” standards ZEISS T* Coating will be equipped with Multi-ALD technology ...