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» Maximal Discrepancy for Support Vector Machines
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DAM
2008
83views more  DAM 2008»
14 years 9 months ago
Multi-group support vector machines with measurement costs: A biobjective approach
Support Vector Machine has shown to have good performance in many practical classification settings. In this paper we propose, for multi-group classification, a biobjective optimi...
Emilio Carrizosa, Belen Martin-Barragan, Dolores R...
CCCG
2008
14 years 11 months ago
The Solution Path of the Slab Support Vector Machine
Given a set of points in a Hilbert space that can be separated from the origin. The slab support vector machine (slab SVM) is an optimization problem that aims at finding a slab (...
Joachim Giesen, Madhusudan Manjunath, Michael Eige...
NIPS
2003
14 years 11 months ago
Margin Maximizing Loss Functions
Margin maximizing properties play an important role in the analysis of classi£cation models, such as boosting and support vector machines. Margin maximization is theoretically in...
Saharon Rosset, Ji Zhu, Trevor Hastie
IJON
2010
148views more  IJON 2010»
14 years 8 months ago
Modeling radiation-induced lung injury risk with an ensemble of support vector machines
Radiation-induced lung injury, radiation pneumonitis (RP), is a potentially fatal side-effect of thoracic radiation therapy. In this work, using an ensemble of support vector mac...
Todd W. Schiller, Yixin Chen, Issam El-Naqa, Josep...
99
Voted
ML
2002
ACM
220views Machine Learning» more  ML 2002»
14 years 9 months ago
Bayesian Methods for Support Vector Machines: Evidence and Predictive Class Probabilities
I describe a framework for interpreting Support Vector Machines (SVMs) as maximum a posteriori (MAP) solutions to inference problems with Gaussian Process priors. This probabilisti...
Peter Sollich