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PKDD
2009
Springer
138views Data Mining» more  PKDD 2009»
15 years 4 months ago
Margin and Radius Based Multiple Kernel Learning
A serious drawback of kernel methods, and Support Vector Machines (SVM) in particular, is the difficulty in choosing a suitable kernel function for a given dataset. One of the appr...
Huyen Do, Alexandros Kalousis, Adam Woznica, Melan...
KDD
2006
ACM
149views Data Mining» more  KDD 2006»
15 years 10 months ago
Regularized discriminant analysis for high dimensional, low sample size data
Linear and Quadratic Discriminant Analysis have been used widely in many areas of data mining, machine learning, and bioinformatics. Friedman proposed a compromise between Linear ...
Jieping Ye, Tie Wang
126
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KDD
2012
ACM
205views Data Mining» more  KDD 2012»
13 years 4 days ago
Rank-loss support instance machines for MIML instance annotation
Multi-instance multi-label learning (MIML) is a framework for supervised classification where the objects to be classified are bags of instances associated with multiple labels....
Forrest Briggs, Xiaoli Z. Fern, Raviv Raich
KDD
2005
ACM
125views Data Mining» more  KDD 2005»
15 years 10 months ago
Email data cleaning
Addressed in this paper is the issue of `email data cleaning' for text mining. Many text mining applications need take emails as input. Email data is usually noisy and thus i...
Jie Tang, Hang Li, Yunbo Cao, ZhaoHui Tang
PKDD
2010
Springer
160views Data Mining» more  PKDD 2010»
14 years 8 months ago
Entropy and Margin Maximization for Structured Output Learning
Abstract. We consider the problem of training discriminative structured output predictors, such as conditional random fields (CRFs) and structured support vector machines (SSVMs)....
Patrick Pletscher, Cheng Soon Ong, Joachim M. Buhm...