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STOC
2004
ACM
126views Algorithms» more  STOC 2004»
14 years 8 months ago
Bypassing the embedding: algorithms for low dimensional metrics
The doubling dimension of a metric is the smallest k such that any ball of radius 2r can be covered using 2k balls of raThis concept for abstract metrics has been proposed as a na...
Kunal Talwar
SISAP
2008
IEEE
175views Data Mining» more  SISAP 2008»
14 years 2 months ago
Anytime K-Nearest Neighbor Search for Database Applications
Many contemporary database applications require similarity-based retrieval of complex objects where the only usable knowledge of its domain is determined by a metric distance func...
Weijia Xu, Daniel P. Miranker, Rui Mao, Smriti R. ...
COMPGEOM
2011
ACM
12 years 11 months ago
Metric graph reconstruction from noisy data
Many real-world data sets can be viewed of as noisy samples of special types of metric spaces called metric graphs [16]. Building on the notions of correspondence and GromovHausdo...
Mridul Aanjaneya, Frédéric Chazal, D...
CIKM
2009
Springer
14 years 2 months ago
Maximal metric margin partitioning for similarity search indexes
We propose a partitioning scheme for similarity search indexes that is called Maximal Metric Margin Partitioning (MMMP). MMMP divides the data on the basis of its distribution pat...
Hisashi Kurasawa, Daiji Fukagawa, Atsuhiro Takasu,...
ICIP
2007
IEEE
14 years 1 months ago
Adaptive Cluster-Distance Bounding for Nearest Neighbor Search in Image Databases
We consider approaches for exact similarity search in a high dimensional space of correlated features representing image datasets, based on principles of clustering and vector qua...
Sharadh Ramaswamy, Kenneth Rose