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Estimation of Dependences Based on Empirical Data [in Russian] [1%] by admin, 2007-01-31 11:08
In this book, the original ``Generalized Portrait'' Algorithm for constructing separating hyperplanes with optimal margin is described.
duplicates [1%] by admin, 2007-01-31 11:08
Properties of Support Vector Machines [1%] by admin, 2007-01-31 11:08
Shrinking the tube: a new support vector regression algorithm [1%] by admin, 2007-01-31 11:08
Exploiting generative models in discriminative classifiers [1%] by admin, 2007-01-31 11:08
Probabilistic Kernel Regression Models [1%] by admin, 2007-01-31 11:08
Semi-Supervised Support Vector Machines [1%] by admin, 2007-01-31 11:08
Data Discrimination via Nonlinear Generalized Support Vector Machines [1%] by admin, 2007-01-31 11:08
Regularized Principal Manifolds [1%] by admin, 2007-01-31 11:08
Classification on proximity data with LP-machines [1%] by admin, 2007-01-31 11:08
We provide a new linear program to deal with classification of data in the case of functions written in terms of pairwise proximities. This allows to ...
Linear programs for automatic accuracy control in regression [1%] by admin, 2007-01-31 11:08
We have recently proposed a new approach to control the number of basis functions and the accuracy in Support Vector Machines. The latter is ...
A fast iterative nearest point algorithm for support vector machine classifier design [1%] by admin, 2007-01-31 11:08
In this paper we give a new, fast iterative algorithm for support vector machine (SVM) classifier design. The problem is converted to a problem of ...
Generalization Bounds via Eigenvalues of the Gram matrix [1%] by admin, 2007-01-31 11:08
Statistical Mechanics of Support Vector Networks [1%] by admin, 2007-01-31 11:08
Using methods of statistical physics, we investigate the generalization performance of SVMs. For nonlinear classification rules, the generalization ...
Support vector classifier with asymmetric kernel function [1%] by admin, 2007-01-31 11:08
Optimal Hyperplane Classifier with Adaptive Norm [1%] by admin, 2007-01-31 11:08
We propose the optimal hyperplane classifier in which the norm also adapts for learning. Both hyperplane and norm parameters are optimized so that the ...
Improved Generalization via Tolerant Training [1%] by admin, 2007-01-31 11:08
Theoretical and computational justification is given for improved generalization when the training set is learned with less accuracy. The model used ...
View-based 3D object recognition with Support Vector Machines [1%] by admin, 2007-01-31 11:08
Some of the good results reported on SVMs for 3D object recognition are confirmed, while we compare the results with a Nearest Neighbor classifier and ...
Properties of Support Vector Machines for Regression [1%] by admin, 2007-01-31 11:08
In this report we show that minimizing the norm of $w^2$ is equivalent to maximizing the sparsity of the representation of the optimal approximating ...
Classification Properties of Support Vector Machines for Regression [1%] by admin, 2007-01-31 11:08
In the same hypotheses of the Pontil's theorem, we show that the optimal approximating hyperplane solution of SVMR classifies the data. Moreover, the ...
SUPANOVA - A Sparse, Transparent Modelling Approach [1%] by admin, 2007-01-31 11:08
This work describes a transparent, non-linear, modelling approach that enables constructed models to be visualised, enhancing their validation and ...
The analysis of decomposition methods for support vector machines [1%] by admin, 2007-01-31 11:08
The support vector machine generally requires the solution of a large dense quadratic programming problem. Up to now, very few methods can handle the ...
Input Space vs. Feature Space in Kernel-Based Methods [1%] by admin, 2007-01-31 11:08
Formulations of Support Vector Machines: a Note from an Optimization Point of View [1%] by admin, 2007-01-31 11:08
Support vector method for novelty detection [1%] by admin, 2007-01-31 11:08
Improving the Generalisation of Linear Support Vector Machines: an Application to 3D Object Recognition with Cluttered Background [1%] by admin, 2007-01-31 11:08
Three methods for improving the generalisation of linear SVMs are proposed in the case some dimensions in the data can be considered irrelevant for the ...
Support Vector Machine Classification of Microarray Gene Expression Data [1%] by admin, 2007-01-31 11:08
We introduce a new method of functionally classifying genes using gene expression data from DNA microarray hybridization experiments. The method is ...
On margin and support vector separability in Support Vector Machines for Regression [1%] by admin, 2007-01-31 11:08
We show that when $\epsilon$ is close to 0, there exists a complete analogy between SVMR and SVMR, and the $\epsilon$-tube plays the same role as the ...
Improvements to Platt's SMO Algorithm for SVM Classifier Design [1%] by admin, 2007-01-31 11:08
This paper points out an important source of confusion and inefficiency in Platt's Sequential Minimal Optimization (SMO) algorithm that is caused by ...
Using Class-Center Vectors to Build Support Vector Machines [1%] by admin, 2007-01-31 11:08
Suggests a modified version of SVM which can deal with noise and outliers in the training set better.

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