S
Sunil Arya
Researcher at Hong Kong University of Science and Technology
Publications - 74
Citations - 6777
Sunil Arya is an academic researcher from Hong Kong University of Science and Technology. The author has contributed to research in topics: Convex body & Polytope. The author has an hindex of 27, co-authored 72 publications receiving 6575 citations. Previous affiliations of Sunil Arya include Max Planck Society & All India Institute of Medical Sciences.
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An optimal algorithm for approximate nearest neighbor searching fixed dimensions
TL;DR: In this paper, it was shown that given an integer k ≥ 1, (1 + ϵ)-approximation to the k nearest neighbors of q can be computed in additional O(kd log n) time.
Proceedings ArticleDOI
An optimal algorithm for approximate nearest neighbor searching
TL;DR: It is shown that it is possible to preprocess a set of data points in real D-dimensional space in O(kd) time and in additional space, so that given a query point q, the closest point of S to S to q can be reported quickly.
ANN: library for approximate nearest neighbor searching
Sunil Arya,David M. Mount +1 more
TL;DR: ANN is a library of C++ objects and procedures that supports approximate nearest neighbor searching, and is written as a testbed for a class of nearest neighbour searching algorithms, particularly those based on orthogonal decompositions of space.
Proceedings ArticleDOI
Approximate nearest neighbor queries in fixed dimensions
Sunil Arya,David M. Mount +1 more
TL;DR: A practical variant of this algorithm is implemented, and it is shown empirically that for many point distributions this variant of the algorithm finds the nearest neighbor in moderately large dimension significantly faster than existing practical approaches.
Journal ArticleDOI
Space-time tradeoffs for approximate nearest neighbor searching
TL;DR: There is a single approach to nearest neighbor searching, which both improves upon existing results and spans the spectrum of space-time tradeoffs, and new algorithms for constructing AVDs and tools for analyzing their total space requirements are provided.