A Neural Algorithm for Similarity Search

A Neural Algorithm for Similarity Search

February 7, 2018


727 E. Tyler St.
Tempe, AZ 85287


Biodesign Institute, AL1-10/14

Date and Time

February 13, 2018, 2:30 pm (Length: 1 hour 0 minutes)

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Saket Navlakha, Ph.D., Assistant Professor, Integrative Biology Laboratory, Pioneer Fund Developmental Chair, Salk Institute

Similarity search, such as identifying similar images in a database or similar documents on the web, is a fundamental computing problem faced by many large-scale information retrieval systems. Navlakha’s lab discovered that the fly’s olfactory circuit solves this problem using a novel variant of a traditional computer science algorithm (called locality-sensitive hashing). The fly’s circuit assigns similar neural activity patterns to similar input stimuli (odors), so that behaviors learned from one odor can be applied when a similar odor is experienced. Overall, this perspective helps illuminate the logic supporting an important sensory function (olfaction), and it provides a conceptually new algorithm for solving a fundamental computational problem. This is joint work with Charles F. Stevens and Sanjoy Dasgupta.

Host: Andrea Richa, and the Biodesign Center for Biocomputing, Security and Society