Mediaspace scheduled maintenance: Aug 25, 2026 07:00 - 12:00 AM. During this time, videos will be temporarily unavailable. Check status updates.

Publication

Online Policy Adaptation for Ensemble Classifiers

Samy Bengio, Christos Dimitrakakis
2005
Journal Articles

Résumé

Ensemble algorithms can improve the performance of a given learning algorithm through the combination of multiple base classifiers into an ensemble. In this paper we attempt to train and combine the base classifiers using an adaptive policy. This policy is learnt through a $Q$ -learning inspired technique. Its effectiveness for an essentially supervised task is demonstrated by experimental results on several UCI benchmark databases.

Source officielle

https://infoscience.epfl.ch/entities/publication/e4b81f9f-42b0-471f-bca6-94cbdee38645

À propos de ce résultat

Cette page est générée automatiquement et peut contenir des informations qui ne sont pas correctes, complètes, à jour ou pertinentes par rapport à votre recherche. Il en va de même pour toutes les autres pages de ce site. Veillez à vérifier les informations auprès des sources officielles de l'EPFL.

Samy Bengio, Christos Dimitrakakis
2005
Journal Articles

Résumé

Source officielle

https://infoscience.epfl.ch/entities/publication/e4b81f9f-42b0-471f-bca6-94cbdee38645

À propos de ce résultat

Concepts associés (29)

Apprentissage ensembliste

In statistics and machine learning, ensemble methods use multiple learning algorithms to obtain better predictive performance than could be obtained from any of the constituent learning algorithms alone. Unlike a statistical ensemble in statistical mechanics, which is usually infinite, a machine learning ensemble consists of only a concrete finite set of alternative models, but typically allows for much more flexible structure to exist among those alternatives.

Policy

Policy is a deliberate system of guidelines to guide decisions and achieve rational outcomes. A policy is a statement of intent and is implemented as a procedure or protocol. Policies are generally adopted by a governance body within an organization. Policies can assist in both subjective and objective decision making. Policies used in subjective decision-making usually assist senior management with decisions that must be based on the relative merits of a number of factors, and as a result, are often hard to test objectively, e.

Boosting

Le boosting est un domaine de l'apprentissage automatique (branche de l'intelligence artificielle). C'est un principe qui regroupe de nombreux algorithmes qui s'appuient sur des ensembles de classifieurs binaires : le boosting optimise leurs performances. Le principe est issu de la combinaison de classifieurs (appelés également hypothèses). Par itérations successives, la connaissance d'un classifieur faible - weak classifier - est ajoutée au classifieur final - strong classifier.

Afficher plus

Publications associées (31)

Afficher plus

Online Policy Adaptation for Ensemble Classifiers

Graph Chatbot

Few-shot Learning for Efficient and Effective Machine Learning Model Adaptation

Understanding generalization and robustness in modern deep learning

Topics in statistical physics of high-dimensional machine learning