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Alexei Pozdnoukhov

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Publications associées (12)

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Active learning for monitoring network optimization

Devis Tuia, Alexei Pozdnoukhov

This book provides an introduction to spatio-temporal design that contains a description of one or two basic settings (e.g., migration and biodiversity) that includes real data sets, data-generating mechanisms, and possible simulation scenarios. Furthermor ...

John Wiley & Sons2013

Using active learning for monitoring networks design: the example of wind power plants sites evaluation

Devis Tuia, Alexei Pozdnoukhov

Locating new wind farms is of crucial importance for energy policies of the next decade. To select the new location, an accurate picture of the wind fields is necessary. However, characterizing wind fields is a difficult task, since the phenomenon is highl ...

2012

Prior Knowledge in Kernel Methods

Alexei Pozdnoukhov

Machine Learning is a modern and actively developing field of computer science, devoted to extracting and estimating dependencies from empirical data. It combines such fields as statistics, optimization theory and artificial intelligence. In practical task ...

École Polytechnique Fédérale de Lausanne2006

Prior knowledge in Kernel methods

Alexei Pozdnoukhov

EPFL2006

A Kernel Classifier for Distributions

Samy Bengio, Alexei Pozdnoukhov

This paper presents a new algorithm for classifying distributions. The algorithm combines the principle of margin maximization and a kernel trick, applied to distributions. Thus, it combines the discriminative power of support vector machines and the well- ...

IDIAP2005

Invariances in Kernel Methods: From Samples to Objects

Samy Bengio, Alexei Pozdnoukhov

This paper presents a general method for incorporating prior knowledge into kernel methods such as Support Vector Machines. It applies when the prior knowledge can be formalized by the description of an object around each sample of the training set, assumi ...

IDIAP2004

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

From Samples to Objects in Kernel Methods

Samy Bengio, Alexei Pozdnoukhov

This paper presents a general method for incorporating prior knowledge into kernel methods. It applies when the prior knowledge can be formalized by the description of an object around each sample of the training set, assuming that all points in the given ...

IDIAP2003

Tangent Vector Kernels for Invariant Image Classification with SVMs

Samy Bengio, Alexei Pozdnoukhov

IDIAP2003

The analysis of kernel ridge regression learning algorithm.

Alexei Pozdnoukhov

The paper presents Kernel Ridge Regression, a nonlinear extension of the well known statistical model of ridge regression. New insights on the method are also presented. In particular, the connection between ridge regression and local translation-invariant ...

IDIAP2002