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Riemannian walk for incremental learning: Understanding forgetting and intransigence

Abstract:

Incremental learning (IL) has received a lot of attention recently, however, the literature lacks a precise problem definition, proper evaluation settings, and metrics tailored specifically for the IL problem. One of the main objectives of this work is to fill these gaps so as to provide a common ground for better understanding of IL. The main challenge for an IL algorithm is to update the classifier whilst preserving existing knowledge. We observe that, in addition to forgetting, a known iss...

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Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1007/978-3-030-01252-6_33

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Institution:
University of Oxford
Division:
MPLS Division
Department:
Engineering Science
Role:
Author
More by this author
Institution:
University of Oxford
Division:
MPLS Division
Department:
Engineering Science
Role:
Author
More by this author
Institution:
University of Oxford
Division:
MPLS
Department:
Engineering Science
Role:
Author
Rhodes Trust More from this funder
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Grant:
ERC-2012-AdG-321162-HELIOS
Publisher:
Springer Publisher's website
Journal:
European Conference on Computer Vision (ECCV) 2018 Journal website
Host title:
European Conference on Computer Vision (ECCV) 2018
Publication date:
2018-10-06
Acceptance date:
2018-07-03
DOI:
Source identifiers:
934804
Pubs id:
pubs:934804
UUID:
uuid:092625dd-d31d-43b1-9466-4cc18e8598ea
Local pid:
pubs:934804
Deposit date:
2018-10-26

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