Publication

Laplacian Support Vector Analysis for Subspace Discriminative Learning

Publications associées (62)

Graph Chatbot

Chattez avec Graph Search

Posez n’importe quelle question sur les cours, conférences, exercices, recherches, actualités, etc. de l’EPFL ou essayez les exemples de questions ci-dessous.

AVERTISSEMENT : Le chatbot Graph n'est pas programmé pour fournir des réponses explicites ou catégoriques à vos questions. Il transforme plutôt vos questions en demandes API qui sont distribuées aux différents services informatiques officiellement administrés par l'EPFL. Son but est uniquement de collecter et de recommander des références pertinentes à des contenus que vous pouvez explorer pour vous aider à répondre à vos questions.

Connectez-vous pour utiliser Chat avec Graph Search

Offline Cursive Handwriting: From Word To Text Recognition

Alessandro Vinciarelli

This thesis presents a PhD work on offline cursive handwriting recognition, the automatic transcription of cursive data when only its image is available. Two main approaches were used in the literature to solve the problem. The first one attempts to segmen ...

IDIAP2003

Face Detection using SVM Trained in Eigenfaces Space

Jean-Philippe Thiran, Vlad Popovici

The central problem in the case of face detectors is to build a face class model. We present a method for face class modeling in the eigenfaces space using a large-margin classifier like SVM. Two main issues are addressed: what is the required number of ei ...

SPIE2003

PCA in Autocorrelation Space

Jean-Philippe Thiran, Vlad Popovici

The use of higher order autocorrelations as features for pattern classification has been usually restricted to second or third orders due to high computational costs. Since the autocorrelation space is a high dimensional space we are interested in reducing ...

SPIE2002

Transforming the feature vectors to improve HMM based cursive word recognition systems

Samy Bengio, Alessandro Vinciarelli

Although many Offline Cursive Word Recognition systems are based on HMMs, no attention was ever paid, to our knowledge, to the fact that the feature vectors are typically not in the most suitable form for modeling. They are most of the time correlated and ...

IDIAP2002

Covariance Kernels from Bayesian Generative Models

Matthias Seeger

We propose the framework of mutual information kernels for learning covariance kernels, as used in Support Vector machines and Gaussian process classifiers, from unlabeled task data using Bayesian techniques. We describe an implementation of this framework ...

2002

A new spectral problem in fluid-structure interaction with transpiration

The aim of this Note is to provide a rigorous mathematical treatment of a new spectral problem, coming from a linear stability analysis in fluid-structure interaction. This eigenproblem involves the linearized incompressible Navier-Stokes equations coupled ...

2002

Multiresolution Moment Filters

Michaël Unser, Michael Sühling, Muthuvel Arigovindan

We define multi-scale moments that are estimated locally by analyzing the image through a sliding window at multiple scales. When the analysis window satisfies a two-scale relation, we prove that these moments can be computed very efficiently using a multi ...

IEEE2002

Mixture models for unsupervised and supervised learning

In a society which produces and consumes an ever increasing amount of information, methods which can make sense out of al1 this data become of crucial importance. Machine learning tries to develop models which can make the information load accessible. Thre ...

EPFL2000

Mixture Models for Unsupervised and Supervised Learning

In a society which produces and consumes an ever increasing amount of information, methods which can make sense out of all this data become of crucial importance. Machine learning tries to develop models which can make the information load accessible. Thre ...

IDIAP2000

Mixture Models for Unsupervised and Supervised Learning

École Polytechnique Fédérale de Lausanne, Computer Science Department2000