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The Effect of Co-adaptive Learning & Feedback in Interactive Machine Learning

Zbyszynski, Michael; Di Donato, Balandino and Tanaka, Atau. 2019. 'The Effect of Co-adaptive Learning & Feedback in Interactive Machine Learning'. In: ACM CHI: Human-Centered Machine Learning Perspectives Workshop. Glasgow, United Kingdom 4 May 2019. [Conference or Workshop Item]

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Abstract or Description

In this paper, we consider the effect of co-adaptive learning on the training and evaluation of real-time, interactive machine learning systems, referring to specific examples in our work on action-perception loops, feedback for virtual tasks, and training of regression and temporal models. Through these studies we have encountered challenges when designing and assessing expressive, multimodal interactive systems. We discuss those challenges to machine learning and human-computer interaction, proposing future directions and research.

Item Type:

Conference or Workshop Item (Other)

Keywords:

human-centred machine learning, co-adaptation

Departments, Centres and Research Units:

Computing > Embodied AudioVisual Interaction Group (EAVI)

Dates:

DateEvent
5 March 2019Accepted
4 May 2019Published

Event Location:

Glasgow, United Kingdom

Date range:

4 May 2019

Item ID:

26144

Date Deposited:

03 Apr 2019 13:17

Last Modified:

29 Aug 2019 13:35

URI:

http://research.gold.ac.uk/id/eprint/26144

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