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KDD
2007
ACM
165views Data Mining» more  KDD 2007»
15 years 10 months ago
Finding low-entropy sets and trees from binary data
The discovery of subsets with special properties from binary data has been one of the key themes in pattern discovery. Pattern classes such as frequent itemsets stress the co-occu...
Eino Hinkkanen, Hannes Heikinheimo, Heikki Mannila...
PAMI
2008
156views more  PAMI 2008»
14 years 9 months ago
Tied Factor Analysis for Face Recognition across Large Pose Differences
Face recognition algorithms perform very unreliably when the pose of the probe face is different from the gallery face: typical feature vectors vary more with pose than with identi...
Simon J. D. Prince, James H. Elder, Jonathan Warre...
TIFS
2008
129views more  TIFS 2008»
14 years 9 months ago
On Empirical Recognition Capacity of Biometric Systems Under Global PCA and ICA Encoding
Performance of biometric-based recognition systems depends on various factors: database quality, image preprocessing, encoding techniques, etc. Given a biometric database and a se...
Natalia A. Schmid, Francesco Nicolo
BMCBI
2006
147views more  BMCBI 2006»
14 years 9 months ago
Grouping Gene Ontology terms to improve the assessment of gene set enrichment in microarray data
Background: Gene Ontology (GO) terms are often used to assess the results of microarray experiments. The most common way to do this is to perform Fisher's exact tests to find...
Alex Lewin, Ian C. Grieve
PODS
2005
ACM
151views Database» more  PODS 2005»
15 years 9 months ago
Estimating arbitrary subset sums with few probes
Suppose we have a large table T of items i, each with a weight wi, e.g., people and their salary. In a general preprocessing step for estimating arbitrary subset sums, we assign e...
Noga Alon, Nick G. Duffield, Carsten Lund, Mikkel ...