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» On the Learnability of Vector Spaces
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SIGMOD
2006
ACM
127views Database» more  SIGMOD 2006»
15 years 10 months ago
Efficient reverse k-nearest neighbor search in arbitrary metric spaces
The reverse k-nearest neighbor (RkNN) problem, i.e. finding all objects in a data set the k-nearest neighbors of which include a specified query object, is a generalization of the...
Elke Achtert, Christian Böhm, Peer Kröge...
ALT
2008
Springer
15 years 6 months ago
Nonparametric Independence Tests: Space Partitioning and Kernel Approaches
Abstract. Three simple and explicit procedures for testing the independence of two multi-dimensional random variables are described. Two of the associated test statistics (L1, log-...
Arthur Gretton, László Györfi
106
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ESWS
2008
Springer
14 years 11 months ago
Conceptual Situation Spaces for Semantic Situation-Driven Processes
Context-awareness is a highly desired feature across several application domains. Semantic Web Services (SWS) technologies address context-adaptation by enabling the automatic disc...
Stefan Dietze, Alessio Gugliotta, John Domingue
JMLR
2002
137views more  JMLR 2002»
14 years 9 months ago
The Subspace Information Criterion for Infinite Dimensional Hypothesis Spaces
A central problem in learning is selection of an appropriate model. This is typically done by estimating the unknown generalization errors of a set of models to be selected from a...
Masashi Sugiyama, Klaus-Robert Müller
ICDE
2007
IEEE
185views Database» more  ICDE 2007»
15 years 11 months ago
On k-Nearest Neighbor Searching in Non-Ordered Discrete Data Spaces
A k-nearest neighbor (k-NN) query retrieves k objects from a database that are considered to be the closest to a given query point. Numerous techniques have been proposed in the p...
Dashiell Kolbe, Qiang Zhu, Sakti Pramanik