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ICDT
2001
ACM
116views Database» more  ICDT 2001»
13 years 10 months ago
On Optimizing Nearest Neighbor Queries in High-Dimensional Data Spaces
Abstract. Nearest-neighbor queries in high-dimensional space are of high importance in various applications, especially in content-based indexing of multimedia data. For an optimiz...
Stefan Berchtold, Christian Böhm, Daniel A. K...
JMLR
2012
11 years 8 months ago
Random Search for Hyper-Parameter Optimization
Grid search and manual search are the most widely used strategies for hyper-parameter optimization. This paper shows empirically and theoretically that randomly chosen trials are ...
James Bergstra, Yoshua Bengio
STOC
2006
ACM
92views Algorithms» more  STOC 2006»
14 years 6 months ago
On the importance of idempotence
Range searching is among the most fundamental problems in computational geometry. An n-element point set in Rd is given along with an assignment of weights to these points from so...
Sunil Arya, Theocharis Malamatos, David M. Mount
KDD
2001
ACM
253views Data Mining» more  KDD 2001»
14 years 6 months ago
GESS: a scalable similarity-join algorithm for mining large data sets in high dimensional spaces
The similarity join is an important operation for mining high-dimensional feature spaces. Given two data sets, the similarity join computes all tuples (x, y) that are within a dis...
Jens-Peter Dittrich, Bernhard Seeger
IPPS
1997
IEEE
13 years 10 months ago
d-Dimensional Range Search on Multicomputers
The range tree is a fundamental data structure for multidimensional point sets, and as such, is central in a wide range of geometric anddatabaseapplications. Inthis paper, we desc...
Afonso Ferreira, Claire Kenyon, Andrew Rau-Chaplin...