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IJCAI
2007
13 years 10 months ago
Simple Training of Dependency Parsers via Structured Boosting
Recently, significant progress has been made on learning structured predictors via coordinated training algorithms such as conditional random fields and maximum margin Markov ne...
Qin Iris Wang, Dekang Lin, Dale Schuurmans
ICDM
2003
IEEE
135views Data Mining» more  ICDM 2003»
14 years 2 months ago
An Algorithm for the Exact Computation of the Centroid of Higher Dimensional Polyhedra and its Application to Kernel Machines
The Support Vector Machine (SVM) solution corresponds to the centre of the largest sphere inscribed in version space. Alternative approaches like Bayesian Point Machines (BPM) and...
Frédéric Maire
ICML
2005
IEEE
14 years 10 months ago
Explanation-Augmented SVM: an approach to incorporating domain knowledge into SVM learning
We introduce a novel approach to incorporating domain knowledge into Support Vector Machines to improve their example efficiency. Domain knowledge is used in an Explanation Based ...
Qiang Sun, Gerald DeJong
TNN
2008
133views more  TNN 2008»
13 years 9 months ago
A General Wrapper Approach to Selection of Class-Dependent Features
In this paper, we argue that for a C-class classification problem, C 2-class classifiers, each of which discriminating one class from the other classes and having a characteristic ...
Lipo Wang, Nina Zhou, Feng Chu
JMLR
2010
123views more  JMLR 2010»
13 years 7 months ago
Maximum Relative Margin and Data-Dependent Regularization
Leading classification methods such as support vector machines (SVMs) and their counterparts achieve strong generalization performance by maximizing the margin of separation betw...
Pannagadatta K. Shivaswamy, Tony Jebara