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» Measuring the Diversity of a Test Set With Distance Entropy
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PAMI
2008
197views more  PAMI 2008»
14 years 9 months ago
LEGClust - A Clustering Algorithm Based on Layered Entropic Subgraphs
Hierarchical clustering is a stepwise clustering method usually based on proximity measures between objects or sets of objects from a given data set. The most common proximity meas...
Jorge M. Santos, Joaquim Marques de Sá, Lu&...
ICDM
2007
IEEE
129views Data Mining» more  ICDM 2007»
15 years 3 months ago
A Generalization of Proximity Functions for K-Means
K-means is a widely used partitional clustering method. A large amount of effort has been made on finding better proximity (distance) functions for K-means. However, the common c...
Junjie Wu, Hui Xiong, Jian Chen, Wenjun Zhou
DATE
2009
IEEE
88views Hardware» more  DATE 2009»
15 years 1 months ago
A generic framework for scan capture power reduction in fixed-length symbol-based test compression environment
Growing test data volume and overtesting caused by excessive scan capture power are two of the major concerns for the industry when testing large integrated circuits. Various test...
Xiao Liu, Qiang Xu
176
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ICDE
2003
IEEE
146views Database» more  ICDE 2003»
15 years 11 months ago
Distance Based Indexing for String Proximity Search
In many database applications involving string data, it is common to have near neighbor queries (asking for strings that are similar to a query string) or nearest neighbor queries...
Jai Macker, Murat Tasan, Süleyman Cenk Sahina...
DIS
2007
Springer
15 years 3 months ago
A Hilbert Space Embedding for Distributions
We describe a technique for comparing distributions without the need for density estimation as an intermediate step. Our approach relies on mapping the distributions into a reprodu...
Alexander J. Smola, Arthur Gretton, Le Song, Bernh...