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:	Date Event 5 March 2019 Accepted 4 May 2019 Published
Event Location:	Glasgow, United Kingdom
Date range:	4 May 2019
Item ID:	26144
Date Deposited:	03 Apr 2019 13:17
Last Modified:	11 Jun 2021 18:45
URI:	https://research.gold.ac.uk/id/eprint/26144

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