Renewing the Respect for Similarity

Abstract

In psychology, the concept of similarity has traditionally evoked a mixture of respect, stemmingfrom its ubiquity and intuitive appeal, and concern, due to its dependence on the framing of the problemat hand and on its context. We argue for a renewed focus on similarity as an explanatory concept, bysurveying established results and new developments in the theory and methods of similarity-preservingassociative lookup and dimensionality reduction — critical components of many cognitive functions, aswell as of intelligent data management in computer vision. We focus in particular on the growing familyof algorithms that support associative memory by performing hashing that respects local similarity, andon the uses of similarity in representing structured objects and scenes. Insofar as these similarity-basedideas and methods are useful in cognitive modeling and in AI applications, they should be included inthe core conceptual toolkit of computational neuroscience