We show that user-centric learning is beneficial for users who contribute many EMA, while a learner over the whole stream is better for users with few EMA.
We show that user-centric learning is beneficial for users who contribute many EMA, while a learner over the whole stream is better for users with few EMA.
We show that user-centric learning is beneficial for users who contribute many EMA, while a learner over the whole stream is better for users with few EMA.
In this paper we propose two methods to assess the accuracy of the user model. The assumptions about the user might either be compared to an external test, or ...
Apr 11, 2022 · Our main findings are that for EMA prediction the entity-centric predictors should be preferred over a user-insensitive global model and that ...
User-centric vs whole-stream learning for EMA prediction · Date · Authors · Journal Title · Journal ISSN · Volume Title · Publication Type · DOI · Published in.
The main findings are that for EMA prediction the entity-centric predictors should be preferred over a user-insensitive global model and that the choice of ...
... User-centric vs whole-stream learning for EMA prediction. In: (Proceedings of the) IEEE 34th International Symposium on Computer-Based Medical Systems (CBMS) ...
2021, entitled: “User-centric vs whole-stream learning for EMA prediction”, https://ieeexplore.ieee.org/document/9474661). The way users interact with an ...
User-centric vs whole-stream learning for EMA prediction. Conference Paper. Jun 2021. Saijal Shahania · Vishnu Unnikrishnan ...