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NIPS
2007
13 years 8 months ago
A Risk Minimization Principle for a Class of Parzen Estimators
This paper1 explores the use of a Maximal Average Margin (MAM) optimality principle for the design of learning algorithms. It is shown that the application of this risk minimizati...
Kristiaan Pelckmans, Johan A. K. Suykens, Bart De ...
NECO
1998
83views more  NECO 1998»
13 years 7 months ago
Properties of Support Vector Machines
Support Vector Machines (SVMs) perform pattern recognition between two point classes by nding a decision surface determined by certain points of the training set, termed Support V...
Massimiliano Pontil, Alessandro Verri
TNN
2008
76views more  TNN 2008»
13 years 7 months ago
Maxi-Min Margin Machine: Learning Large Margin Classifiers Locally and Globally
Abstract--In this paper, we propose a novel large margin classifier, called the maxi
Kaizhu Huang, Haiqin Yang, Irwin King, Michael R. ...
NIPS
2004
13 years 8 months ago
Maximum Margin Clustering
We propose a new method for clustering based on finding maximum margin hyperplanes through data. By reformulating the problem in terms of the implied equivalence relation matrix, ...
Linli Xu, James Neufeld, Bryce Larson, Dale Schuur...
COLT
2005
Springer
14 years 1 months ago
Margin-Based Ranking Meets Boosting in the Middle
Abstract. We present several results related to ranking. We give a general margin-based bound for ranking based on the L∞ covering number of the hypothesis space. Our bound sugge...
Cynthia Rudin, Corinna Cortes, Mehryar Mohri, Robe...