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» A PAC Bound for Approximate Support Vector Machines
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INFORMATICALT
2011
91views more  INFORMATICALT 2011»
13 years 2 months ago
A Quadratic Loss Multi-Class SVM for which a Radius-Margin Bound Applies
To set the values of the hyperparameters of a support vector machine (SVM), the method of choice is cross-validation. Several upper bounds on the leave-one-out error of the pattern...
Yann Guermeur, Emmanuel Monfrini
ICML
1999
IEEE
14 years 8 months ago
Machine-Learning Applications of Algorithmic Randomness
Most machine learning algorithms share the following drawback: they only output bare predictions but not the con dence in those predictions. In the 1960s algorithmic information t...
Volodya Vovk, Alexander Gammerman, Craig Saunders
ESANN
2007
13 years 8 months ago
Model Selection for Kernel Probit Regression
Abstract. The convex optimisation problem involved in fitting a kernel probit regression (KPR) model can be solved efficiently via an iteratively re-weighted least-squares (IRWLS)...
Gavin C. Cawley
SODA
2001
ACM
102views Algorithms» more  SODA 2001»
13 years 8 months ago
Approximate majorization and fair online load balancing
This paper relates the notion of fairness in online routing and load balancing to vector majorization as developed by Hardy, Littlewood, and Polya 9]. We de ne -supermajorization ...
Ashish Goel, Adam Meyerson, Serge A. Plotkin
ECCC
2010
124views more  ECCC 2010»
13 years 7 months ago
Lower Bounds and Hardness Amplification for Learning Shallow Monotone Formulas
Much work has been done on learning various classes of "simple" monotone functions under the uniform distribution. In this paper we give the first unconditional lower bo...
Vitaly Feldman, Homin K. Lee, Rocco A. Servedio