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BMCBI
2007
178views more  BMCBI 2007»
15 years 13 days ago
SVM clustering
Background: Support Vector Machines (SVMs) provide a powerful method for classification (supervised learning). Use of SVMs for clustering (unsupervised learning) is now being cons...
Stephen Winters-Hilt, Sam Merat
ICDM
2009
IEEE
172views Data Mining» more  ICDM 2009»
14 years 10 months ago
Evaluating Statistical Tests for Within-Network Classifiers of Relational Data
Recently a number of modeling techniques have been developed for data mining and machine learning in relational and network domains where the instances are not independent and ide...
Jennifer Neville, Brian Gallagher, Tina Eliassi-Ra...
CEAS
2006
Springer
15 years 4 months ago
Fast Uncertainty Sampling for Labeling Large E-mail Corpora
One of the biggest challenges in building effective anti-spam solutions is designing systems to defend against the everevolving bag of tricks spammers use to defeat them. Because ...
Richard Segal, Ted Markowitz, William Arnold
ICIP
2008
IEEE
16 years 2 months ago
Implicit spatial inference with sparse local features
This paper introduces a novel way to leverage the implicit geometry of sparse local features (e.g. SIFT operator) for the purposes of object detection and segmentation. A two-clas...
Deirdre O'Regan, Anil C. Kokaram
ICIP
2003
IEEE
16 years 2 months ago
Evaluation strategies for automatic linguistic indexing of pictures
With the rapid technological advances in machine learning and data mining, it is now possible to train computers with hundreds of semantic concepts for the purpose of annotating i...
James Ze Wang, Jia Li, Sui Ching Lin