A neural algorithm for a fundamental computing problem

Similarity search-for example, identifying similar images in a database or similar documents on the web-is a fundamental computing problem faced by large-scale information retrieval systems. We discovered that the fruit fly olfactory circuit solves this problem with a variant of a computer science a...

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Vydané v:Science (American Association for the Advancement of Science) Ročník 358; číslo 6364; s. 793
Hlavní autori: Dasgupta, Sanjoy, Stevens, Charles F, Navlakha, Saket
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: United States 10.11.2017
Predmet:
Algorithms
Animals
Drosophila
Nerve Net
Neural Networks (Computer)
Odorants
Olfactory Cortex
Smell
ISSN:1095-9203, 1095-9203
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Shrnutí:Similarity search-for example, identifying similar images in a database or similar documents on the web-is a fundamental computing problem faced by large-scale information retrieval systems. We discovered that the fruit fly olfactory circuit solves this problem with a variant of a computer science algorithm (called locality-sensitive hashing). The fly circuit assigns similar neural activity patterns to similar odors, so that behaviors learned from one odor can be applied when a similar odor is experienced. The fly algorithm, however, uses three computational strategies that depart from traditional approaches. These strategies can be translated to improve the performance of computational similarity searches. This perspective helps illuminate the logic supporting an important sensory function and provides a conceptually new algorithm for solving a fundamental computational problem.
Bibliografia:ObjectType-Article-1
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ISSN:1095-9203
1095-9203
DOI:10.1126/science.aam9868