资源论文Randomized Algorithms for Comparison-based Search

Randomized Algorithms for Comparison-based Search

2020-01-08 | |  70 |   47 |   0

Abstract

This paper addresses the problem of finding the nearest neighbor (or one of the R-nearest neighbors) of a query object q in a database of n objects, when we can only use a comparison oracle. The comparison oracle, given two reference objects and a query object, returns the reference object most similar to the query object. The main problem we study is how to search the database for the nearest neighbor (NN) of a query, while minimizing the questions. The difficulty of this problem depends on properties of the underlying database. We show the importance of a characterization: combinatorial disorder D which defines approximate triangle n inequalities on ranks. We present a lower bound of 图片.png average number of questions in the search phase for any randomized algorithm, which demonstrates the fundamental role of D for worst case behavior. We develop 3 a randomized scheme for NN retrieval in 图片.png questions. The learning requires asking 图片.png questions and 图片.png bits to store.

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