The development of low-loss reconfigurable integrated optical devices enables further research into technologies including photonic signal processing, analogue quantum computing, and optical neural ...

Presenting an algorithm that solves linear systems with sparse coefficient matrices asymptotically faster than matrix multiplication for any ω > 2. Our algorithm can be viewed as an efficient, ...

data point (a.k.a. training case): One item of data; affinity propagation clusters data points exemplar: A data point that is nicely representative of itself and some other data points. similarity: ...

General sparse matrix–matrix multiplication (SpGEMM) is integral to many high-performance computing (HPC) and machine learning applications. However, prior field-programmable gate array (FPGA)-based ...

Leopard is a fast, modern implementation of sparse, multifrontal symmetric indefinite matrix factorization. It lets you factorize and solve for large sparse matrices much faster than what is possible ...

The first is a sparse dictionary learning algorithm in order to estimate Green’s function vectors between focal or source points in the image window and receiver locations on the array. The second is ...