Searched for: subject%3A%22incentives%22
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Zhan, Juhong (author), Jiang, Yue (author), Cieri, Christopher (author), Liberman, Mark (author), Yuan, Jiahong (author), Chen, Yiya (author), Scharenborg, O.E. (author)
This paper describes our use of mixed incentives and the citizen science portal LanguageARC to prepare, collect and quality control a large corpus of object namings for the purpose of providing speech data to document the under-represented Guanzhong dialect of Chinese spoken in the Shaanxi province in the environs of Xi’an.
conference paper 2022
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Huang, J. (author), Talbi, Rania (author), Zhao, Z. (author), Boucchenak, Sara (author), Chen, Lydia Y. (author), Roos, S. (author)
Federated Learning is an emerging distributed collaborative learning paradigm adopted by many of today's applications, e.g., keyboard prediction and object recognition. Its core principle is to learn from large amount of users data while preserving data privacy by design as collaborative users only need to share the machine learning models...
conference paper 2020
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Jia, L. (author), Chen, X (author), Chu, X (author), Pouwelse, J.A. (author), Epema, D.H.J. (author)
Many private BitTorrent communities employ Sharing Ratio Enforcement<br/>(SRE) schemes to incentivize users to contribute. It has been demonstrated<br/>that users in private communities are highly dedicated and that they seed much<br/>longer than users in communities where SRE is not employed. While most pre-<br/>vious studies focus on showing...
journal article 2014