Model selection for svm Our intent works Songcan Chen Feb.8,2012
Model Selection for SVM & Our intent works Songcan Chen Feb. 8, 2012
Outline Model selection for svm Our intent works
Outline • Model Selection for SVM • Our intent works
Model selection for svm Introduction to 2 works
Model Selection for SVM • Introduction to 2 works
Introduction to 2 works 1. Model selection for primal SVM [MBB11, MLJ111 2. Selection of Hypothesis Space Selecting the Hypothesis Space for Improving the Generalization ability of Support Vector Machines [AGOR11, IJCNN20111 The Impact of Unlabeled patterns in Rademacher Complexity Theory for Kernel Classifiers [AGOR11, NIPS20111
Introduction to 2 works 1. Model selection for primal SVM [MBB11, MLJ11] 2. Selection of Hypothesis Space • Selecting the Hypothesis Space for Improving the Generalization Ability of Support Vector Machines [AGOR11,IJCNN2011] • The Impact of Unlabeled Patterns in Rademacher Complexity Theory for Kernel Classifiers [AGOR11,NIPS2011]
1st work Model selection for primal sV [MBB11, MLJ111 IMBBllGregory Moore Charles bergeron Kristin P. Bennett Machine Learning(2011)85: 175-208
1 st work • Model selection for primal SVM [MBB11, MLJ11] [MBB11] Gregory Moore · Charles Bergeron · Kristin P. Bennett, Machine Learning (2011) 85:175–208