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ICPR
2004
IEEE
16 years 5 months ago
Optimally Regularised Kernel Fisher Discriminant Analysis
Mika et al. [3] introduce a non-linear formulation of Fisher's linear discriminant, based the now familiar "kernel trick", demonstrating state-of-the-art performanc...
Gavin C. Cawley, Kamel Saadi, Nicola L. C. Talbot
ADMA
2009
Springer
246views Data Mining» more  ADMA 2009»
15 years 11 months ago
Semi Supervised Image Spam Hunter: A Regularized Discriminant EM Approach
Image spam is a new trend in the family of email spams. The new image spams employ a variety of image processing technologies to create random noises. In this paper, we propose a s...
Yan Gao, Ming Yang, Alok N. Choudhary
CEAS
2006
Springer
15 years 8 months ago
Online Discriminative Spam Filter Training
We describe a very simple technique for discriminatively training a spam filter. Our results on the TREC Enron spam corpus would have been the best for the Ham at .1% measure, and...
Joshua Goodman, Wen-tau Yih
EMNLP
2008
15 years 5 months ago
Discriminative Learning of Selectional Preference from Unlabeled Text
We present a discriminative method for learning selectional preferences from unlabeled text. Positive examples are taken from observed predicate-argument pairs, while negatives ar...
Shane Bergsma, Dekang Lin, Randy Goebel
NAACL
2004
15 years 5 months ago
Name Tagging with Word Clusters and Discriminative Training
We present a technique for augmenting annotated training data with hierarchical word clusters that are automatically derived from a large unannotated corpus. Cluster membership is...
Scott Miller, Jethran Guinness, Alex Zamanian