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110
Voted
ICML
2008
IEEE
16 years 4 months ago
Stopping conditions for exact computation of leave-one-out error in support vector machines
We propose a new stopping condition for a Support Vector Machine (SVM) solver which precisely reflects the objective of the Leave-OneOut error computation. The stopping condition ...
Klaus-Robert Müller, Pavel Laskov, Vojtech Fr...
117
Voted
ICML
2004
IEEE
16 years 4 months ago
Online and batch learning of pseudo-metrics
We describe and analyze an online algorithm for supervised learning of pseudo-metrics. The algorithm receives pairs of instances and predicts their similarity according to a pseud...
Shai Shalev-Shwartz, Yoram Singer, Andrew Y. Ng
141
Voted
IJCNN
2000
IEEE
15 years 8 months ago
Support Vector Machine for Regression and Applications to Financial Forecasting
The main purpose of this paper is to compare the support vector machine (SVM) developed by Vapnik with other techniques such as Backpropagation and Radial Basis Function (RBF) Net...
Theodore B. Trafalis, Huseyin Ince
109
Voted
IJON
2006
104views more  IJON 2006»
15 years 3 months ago
Kernel methods and the exponential family
The success of Support Vector Machine (SVM) gave rise to the development of a new class of theoretically elegant learning machines which use a central concept of kernels and the a...
Stéphane Canu, Alexander J. Smola
136
Voted
ICML
2009
IEEE
15 years 10 months ago
Rule learning with monotonicity constraints
In classification with monotonicity constraints, it is assumed that the class label should increase with increasing values on the attributes. In this paper we aim at formalizing ...
Wojciech Kotlowski, Roman Slowinski