93 search results - page 10 / 19 » Maximal Discrepancy for Support Vector Machines |
ICML
2004
IEEE
14 years 8 months ago
2004
IEEE
We propose to study links between three important classification algorithms: Perceptrons, Multi-Layer Perceptrons (MLPs) and Support Vector Machines (SVMs). We first study ways to...
NIPS
2007
13 years 8 months ago
2007
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...
IJPRAI
2010
13 years 5 months ago
2010
: AUC-SVM directly maximizes the area under the ROC curve (AUC) through minimizing its hinge loss relaxation, and the decision function is determined by those support vector sample...
JMLR
2012
11 years 9 months ago
2012
We propose a new family of latent variable models called max-margin min-entropy (m3e) models, which define a distribution over the output and the hidden variables conditioned on ...
ICIAR
2004
Springer
14 years 22 days ago
2004
Springer
We present an information theoretic approach for learning a linear dimension reduction transform for object classification. The theoretic guidance of the approach is that the trans...