Bayesian Feature Weighting for Unsupervised Learning‚ with Application to Object Recognition

Bibliographic Details
Main Authors: Carbonetto, P, de Freitas, N, Gustafson, P, Thompson, N
Format: Conference item
Published: 2003
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author Carbonetto, P
de Freitas, N
Gustafson, P
Thompson, N
author_facet Carbonetto, P
de Freitas, N
Gustafson, P
Thompson, N
author_sort Carbonetto, P
collection OXFORD
description
first_indexed 2024-03-07T03:24:54Z
format Conference item
id oxford-uuid:b8b6745f-c831-4359-a019-d75385b9dc53
institution University of Oxford
last_indexed 2024-03-07T03:24:54Z
publishDate 2003
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spelling oxford-uuid:b8b6745f-c831-4359-a019-d75385b9dc532022-03-27T04:57:39ZBayesian Feature Weighting for Unsupervised Learning‚ with Application to Object RecognitionConference itemhttp://purl.org/coar/resource_type/c_5794uuid:b8b6745f-c831-4359-a019-d75385b9dc53Department of Computer Science2003Carbonetto, Pde Freitas, NGustafson, PThompson, N
spellingShingle Carbonetto, P
de Freitas, N
Gustafson, P
Thompson, N
Bayesian Feature Weighting for Unsupervised Learning‚ with Application to Object Recognition
title Bayesian Feature Weighting for Unsupervised Learning‚ with Application to Object Recognition
title_full Bayesian Feature Weighting for Unsupervised Learning‚ with Application to Object Recognition
title_fullStr Bayesian Feature Weighting for Unsupervised Learning‚ with Application to Object Recognition
title_full_unstemmed Bayesian Feature Weighting for Unsupervised Learning‚ with Application to Object Recognition
title_short Bayesian Feature Weighting for Unsupervised Learning‚ with Application to Object Recognition
title_sort bayesian feature weighting for unsupervised learning with application to object recognition
work_keys_str_mv AT carbonettop bayesianfeatureweightingforunsupervisedlearningwithapplicationtoobjectrecognition
AT defreitasn bayesianfeatureweightingforunsupervisedlearningwithapplicationtoobjectrecognition
AT gustafsonp bayesianfeatureweightingforunsupervisedlearningwithapplicationtoobjectrecognition
AT thompsonn bayesianfeatureweightingforunsupervisedlearningwithapplicationtoobjectrecognition