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ISCI
2007
130views more  ISCI 2007»
13 years 9 months ago
Learning to classify e-mail
In this paper we study supervised and semi-supervised classification of e-mails. We consider two tasks: filing e-mails into folders and spam e-mail filtering. Firstly, in a sup...
Irena Koprinska, Josiah Poon, James Clark, Jason C...
ICML
2009
IEEE
14 years 10 months ago
Domain adaptation from multiple sources via auxiliary classifiers
We propose a multiple source domain adaptation method, referred to as Domain Adaptation Machine (DAM), to learn a robust decision function (referred to as target classifier) for l...
Lixin Duan, Ivor W. Tsang, Dong Xu, Tat-Seng Chua
ICDM
2010
IEEE
128views Data Mining» more  ICDM 2010»
13 years 7 months ago
User-Based Active Learning
Active learning has been proven a reliable strategy to reduce manual efforts in training data labeling. Such strategies incorporate the user as oracle: the classifier selects the m...
Christin Seifert, Michael Granitzer
CVPR
2006
IEEE
14 years 12 months ago
A Conic Section Classifier and its Application to Image Datasets
Many problems in computer vision involving recognition and/or classification can be posed in the general framework of supervised learning. There is however one aspect of image dat...
Arunava Banerjee, Santhosh Kodipaka, Baba C. Vemur...
ICPR
2006
IEEE
14 years 11 months ago
Patch-Based Gabor Fisher Classifier for Face Recognition
Face representations based on Gabor features have achieved great success in face recognition, such as Elastic Graph Matching, Gabor Fisher Classifier (GFC), and AdaBoosted Gabor F...
Shiguang Shan, Wen Gao, Xilin Chen, Yu Su