Concept

Hinge loss

Related publications (36)

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CLEF2007 Image Annotation Task: an SVM-based Cue Integration Approach

Barbara Caputo, Tatiana Tommasi

This paper presents the algorithms and results of our participation to the medical image annotation task of ImageCLEFmed 2007. We proposed, as a general strategy, a multi-cue approach where images are represented both by global and local descrip- tors, so ...

2007

Melanoma Recognition Using Representative and Discriminative Kernel Classifiers

Barbara Caputo, Tatiana Tommasi

Malignant melanoma is the most deadly for of skin lesion. Early diagnosis is of critical importance to patient survival. Visual recognition algorithms could potentially be of great help for physicians in a computer assisted diagnosis system. Previous work ...

2006

A Probabilistic Interpretation of SVMs with an Application to Unbalanced Classification

Samy Bengio

In this paper, we show that the hinge loss can be interpreted as the neg-log-likelihood of a semi-parametric model of posterior probabilities. From this point of view, SVMs represent the parametric component of a semi-parametric model fitted by a maximum a ...

IDIAP2005

A Probabilistic Interpretation of SVMs with an Application to Unbalanced Classification

Samy Bengio

2005

The research deals with the novel application of Support Vector Machines (Support Vector Classification and Support Vector Regression) for the analysis and modelling of spatial environmental data. Multiclass classification of soil types and pollution mappi ...

IDIAP2000

Support Vector Machine for Multiclass Classification

Support vector machines (SVMs) are primarily designed for 2-class classification problems. Although in several papers it is mentioned that the combination of

K

SVMs can be used to solve a

K

-class classification problem, such a procedure requires some c ...

IDIAP1998

Support Vector Machine for Multiclass Classification

Support vector machines (SVMs) are primarily designed for 2-class classification problems. Although in several papers it is mentioned that the combination of

K

SVMs can be used to solve a

K

-class classification problem, such a procedure requires some c ...

IDIAP1998