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A Feature Space Foc...
A Feature Space Focus in Machine Teaching
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- Holmberg, Lars (författare)
- Malmö universitet,Institutionen för datavetenskap och medieteknik (DVMT),Internet of Things and People (IOTAP)
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- Davidsson, Paul (författare)
- Malmö universitet,Institutionen för datavetenskap och medieteknik (DVMT),Internet of Things and People (IOTAP)
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- Linde, Per (författare)
- Malmö universitet,Institutionen för konst, kultur och kommunikation (K3),Internet of Things and People (IOTAP)
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(creator_code:org_t)
- 2020
- 2020
- Engelska.
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Ingår i: 2020 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops). - 9781728147161 - 9781728147178
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https://mau.diva-por... (primary) (Raw object)
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https://urn.kb.se/re...
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https://doi.org/10.1...
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Abstract
Ämnesord
Stäng
- Contemporary Machine Learning (ML) often focuseson large existing and labeled datasets and metrics aroundaccuracy and performance. In pervasive online systems, conditionschange constantly and there is a need for systems thatcan adapt. In Machine Teaching (MT) a human domain expertis responsible for the knowledge transfer and can thus addressthis. In my work, I focus on domain experts and the importanceof, for the ML system, available features and the space they span.This space confines the, to the ML systems, observable fragmentof the physical world. My investigation of the feature space isgrounded in a conducted study and related theories. The resultof this work is applicable when designing systems where domainexperts have a key role as teachers.
Ämnesord
- TEKNIK OCH TEKNOLOGIER -- Elektroteknik och elektronik -- Datorsystem (hsv//swe)
- ENGINEERING AND TECHNOLOGY -- Electrical Engineering, Electronic Engineering, Information Engineering -- Computer Systems (hsv//eng)
Nyckelord
- Machine learning
- Machine Teaching
- Human in the loop
Publikations- och innehållstyp
- ref (ämneskategori)
- kon (ämneskategori)
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