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Designing Robust Models for Behaviour Prediction using Sparse Data from Mobile Sensing: A Case Study of Office Workers’ Availability for Wellbeing Interventions

Musolesi, M; Kucukozer Cavdar, S; Taskaya-Temizel, T; Mehrotra, A; Tino, P; (2021) Designing Robust Models for Behaviour Prediction using Sparse Data from Mobile Sensing: A Case Study of Office Workers’ Availability for Wellbeing Interventions. ACM Transactions on Computing for Healthcare (In press). Green open access

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Kucokozer_Designing_Robust_Models_Behaviour_Prediction_Sensing_ACM_Health_2021.pdf - Accepted Version

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Type: Article
Title: Designing Robust Models for Behaviour Prediction using Sparse Data from Mobile Sensing: A Case Study of Office Workers’ Availability for Wellbeing Interventions
Open access status: An open access version is available from UCL Discovery
Publisher version: https://dl.acm.org/journal/health
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
UCL classification: UCL
UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science
URI: https://discovery.ucl.ac.uk/id/eprint/10129548
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