Concept

Noyau polynomial

Publications associées (38)

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A Proposal for a Kernel-based Algorithm for Large Vocabulary Continuous Speech Recognition

We present a proposal of a kernel-based model for large vocabulary continuous speech recognizer. The continuous speech recognition is described as a problem of finding the best phoneme sequence and its best time span, where the phonemes are generated from ...

John Wiley and Sons2009

SVM-based Transfer of Visual Knowledge Across Robotic Platforms

Barbara Caputo, Jie Luo

This paper presents an SVM-based algorithm for the transfer of knowledge across robot platforms aiming to perform the same task. Our method exploits efficiently the transferred knowledge while updating incrementally the internal representation as new infor ...

2007

The More you Learn, the Less you Store: Memory-Controlled Incremental SVM

Barbara Caputo

This paper presents a novel SVM-based algorithm for visual object recognition, capable of learning model representations incrementally. We combine an incremental extension of SVMs with a method which reduces the number of support vectors needed to build th ...

2006

Sparse Gaussian Process Classification With Multiple Classes

Matthias Seeger

Sparse approximations to Bayesian inference for nonparametric Gaussian Process models scale linearly in the number of training points, allowing for the application of these powerful kernel-based models to large datasets. We show how to generalize the binar ...

Department of Statistics, University of Berkeley, CA2004

Tangent Vector Kernels for Invariant Image Classification with SVMs

Samy Bengio, Alexei Pozdnoukhov

This paper presents an application of the general sample-to-object approach to the problem of invariant image classification. The approach results in defining new SVM kernels based on tangent vectors that take into account prior information on known invari ...

2004

Tangent Vector Kernels for Invariant Image Classification with SVMs

Samy Bengio, Alexei Pozdnoukhov

IDIAP2003

Support Vector Machines for Classification and Mapping of Reservoir Data

Alexei Pozdnoukhov

The report deals with the novel application of Support Vector Machines (Support Vectore Classification and Support Vector Regression) for the analysis and modelling of reservoir data. 2 problems are considered: classification and mapping of porosity data. ...

IDIAP2001

Environmental spatial data classification with Support Vector Machines

The report deals with a first application of Support Vector Machines to the environmental spatial data classification. The simplest problem of classification is considered: using original data develop a model for the classification of the regions to be bel ...

IDIAP1999