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CVPR
2008
IEEE
16 years 5 months ago
Semi-Supervised Discriminant Analysis using robust path-based similarity
Linear Discriminant Analysis (LDA), which works by maximizing the within-class similarity and minimizing the between-class similarity simultaneously, is a popular dimensionality r...
Yu Zhang, Dit-Yan Yeung
KDD
2005
ACM
181views Data Mining» more  KDD 2005»
16 years 4 months ago
Evaluating similarity measures: a large-scale study in the orkut social network
Online information services have grown too large for users to navigate without the help of automated tools such as collaborative filtering, which makes recommendations to users ba...
Ellen Spertus, Mehran Sahami, Orkut Buyukkokten
CVPR
2010
IEEE
15 years 2 months ago
Shape-based similarity retrieval of Doppler images for clinical decision support
Flow Doppler imaging has become an integral part of an echocardiographic exam. Automated interpretation of flow doppler imaging has so far been restricted to obtaining hemodynami...
Tanveer Fathima Syeda-Mahmood, Pavan K. Turaga, Da...
SDM
2003
SIAM
110views Data Mining» more  SDM 2003»
15 years 5 months ago
Mixture Models and Frequent Sets: Combining Global and Local Methods for 0-1 Data
We study the interaction between global and local techniques in data mining. Specifically, we study the collections of frequent sets in clusters produced by a probabilistic clust...
Jaakko Hollmén, Jouni K. Seppänen, Hei...
ICCV
2009
IEEE
1019views Computer Vision» more  ICCV 2009»
16 years 8 months ago
Similarity Functions for Categorization: from Monolithic to Category Specific
Similarity metrics that are learned from labeled training data can be advantageous in terms of performance and/or efficiency. These learned metrics can then be used in conjuncti...
Boris Babenko, Steve Branson, Serge Belongie