Introduction to Hyperdimensional Computing
Mike Heddes
University of California, Irvine
Hyperdimensional computing (HD), also known as vector symbolic architectures (VSA), is a computing framework capable of forming compositional distributed representations. HD/VSA forms a "concept space" by exploiting the geometry and algebra of high-dimensional spaces. The central idea is to represent information with randomly generated vectors, called hypervectors. Together with a set of operations on these hypervectors, HD/VSA can represent compositional structures, which, in turn, enables features such as reasoning by analogy and cognitive computing. In this introductory talk, I will introduce the high-dimensional spaces and the fundamental operations on hypervectors. I will then cover applications of HD/VSA such as reasoning by analogy and graph classification.