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Description and evaluation of techniques for transfer learning across sub-categories

Description and evaluation of techniques for transfer learning across sub-categories
Description and evaluation of techniques for transfer learning across sub-categories
This report presents contributions in sub-categorisation. In the first part we propose a simple approach to build a meta-learner on individual classifier that is supposed to implicitly learn class inter-dependencies. We further study how the performance is modified if we add automatically learned meta-classes (group of similar classes). In the second part, we address the problem using a structured learning approach. The main idea is to build a graphical model which efficiently performs labelling at multiple levels simultaneously.
de Campos, Teófilo
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Csurka, Gabriela
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Perronnin, Florent
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McAuley, Julian
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Antenreiter, Martin
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Ortner, Ronald
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Auer, Peter
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Viitaniemi, Ville
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Laaksonen, Jorma
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Pasupa, Kitsuchart
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Saunders, Craig
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Hussain, Zakria
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Shawe-Taylor, John
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de Campos, Teófilo
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Csurka, Gabriela
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Perronnin, Florent
96bc8a08-a10a-432d-b0ce-50b07012df06
McAuley, Julian
a399207a-6fd7-462e-b5d4-189d09e4d5c4
Antenreiter, Martin
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Ortner, Ronald
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Auer, Peter
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Viitaniemi, Ville
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Laaksonen, Jorma
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Pasupa, Kitsuchart
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Saunders, Craig
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Hussain, Zakria
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Shawe-Taylor, John
b1931d97-fdd0-4bc1-89bc-ec01648e928b

de Campos, Teófilo, Csurka, Gabriela, Perronnin, Florent, McAuley, Julian, Antenreiter, Martin, Ortner, Ronald, Auer, Peter, Viitaniemi, Ville, Laaksonen, Jorma, Pasupa, Kitsuchart, Saunders, Craig, Hussain, Zakria and Shawe-Taylor, John (2009) Description and evaluation of techniques for transfer learning across sub-categories

Record type: Monograph (Project Report)

Abstract

This report presents contributions in sub-categorisation. In the first part we propose a simple approach to build a meta-learner on individual classifier that is supposed to implicitly learn class inter-dependencies. We further study how the performance is modified if we add automatically learned meta-classes (group of similar classes). In the second part, we address the problem using a structured learning approach. The main idea is to build a graphical model which efficiently performs labelling at multiple levels simultaneously.

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Published date: 13 October 2009
Organisations: Electronics & Computer Science

Identifiers

Local EPrints ID: 268318
URI: http://eprints.soton.ac.uk/id/eprint/268318
PURE UUID: fe5c6187-090f-4817-94a2-c52ed006febe

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Date deposited: 15 Dec 2009 13:57
Last modified: 14 Mar 2024 09:07

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Contributors

Author: Teófilo de Campos
Author: Gabriela Csurka
Author: Florent Perronnin
Author: Julian McAuley
Author: Martin Antenreiter
Author: Ronald Ortner
Author: Peter Auer
Author: Ville Viitaniemi
Author: Jorma Laaksonen
Author: Kitsuchart Pasupa
Author: Craig Saunders
Author: Zakria Hussain
Author: John Shawe-Taylor

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