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KDD
2009
ACM
150views Data Mining» more  KDD 2009»
14 years 8 months ago
Information theoretic regularization for semi-supervised boosting
We present novel semi-supervised boosting algorithms that incrementally build linear combinations of weak classifiers through generic functional gradient descent using both labele...
Lei Zheng, Shaojun Wang, Yan Liu, Chi-Hoon Lee
CEAS
2007
Springer
13 years 11 months ago
Learning Fast Classifiers for Image Spam
Recently, spammers have proliferated "image spam", emails which contain the text of the spam message in a human readable image instead of the message body, making detect...
Mark Dredze, Reuven Gevaryahu, Ari Elias-Bachrach
FLAIRS
2008
13 years 9 months ago
Evolutionary Learning of Dynamic Naive Bayesian Classifiers
Naive Bayesian classifiers work well in data sets with independent attributes. However, they perform poorly when the attributes are dependent or when there are one or more irrelev...
Miguel A. Palacios-Alonso, Carlos A. Brizuela, Lui...
ICCV
2007
IEEE
14 years 9 months ago
An Invariant Large Margin Nearest Neighbour Classifier
The k-nearest neighbour (kNN) rule is a simple and effective method for multi-way classification that is much used in Computer Vision. However, its performance depends heavily on ...
M. Pawan Kumar, Philip H. S. Torr, Andrew Zisserma...
ICPR
2010
IEEE
13 years 11 months ago
Microaneurysm (MA) Detection Via Sparse Representation Classifier with MA and Non-MA Dictionary Learning
Diabetic retinopathy (DR) is a common complication of diabetes that damages the retina and leads to sight loss if treated late. In its earliest stage, DR can be diagnosed by microa...
Bob Zhang, Lei Zhang, Jane You, Fakhri Karray