118 citations · 234 across the 11 of their papers we have counts for
5 papers · 1 filter
Evaluation and comparison of federated learning algorithms for Human Activity Recognition on smartphones
Sannara Ek, François Portet, Philippe Lalanda +1
Pervasive computing promotes the integration of smart devices in our living spaces to develop services providing assistance to people. Such smart devices are increasingly relying o…
Transformer-based Models to Deal with Heterogeneous Environments in Human Activity Recognition
Sannara EK, François Portet, Philippe Lalanda
Human Activity Recognition (HAR) on mobile devices has been demonstrated to be possible using neural models trained on data collected from the device's inertial measurement units.…
Federated Self-Supervised Learning in Heterogeneous Settings: Limits of a Baseline Approach on HAR
Sannara Ek, Romain Rombourg, François Portet +1
Federated Learning is a new machine learning paradigm dealing with distributed model learning on independent devices. One of the many advantages of federated learning is that train…
Federated Continual Learning through distillation in pervasive computing
Anastasiia Usmanova, François Portet, Philippe Lalanda +1
Federated Learning has been introduced as a new machine learning paradigm enhancing the use of local devices. At a server level, FL regularly aggregates models learned locally on d…
Federated Learning and catastrophic forgetting in pervasive computing: demonstration in HAR domain
Anastasiia Usmanova, François Portet, Philippe Lalanda +1
Federated Learning has been introduced as a new machine learning paradigm enhancing the use of local devices. At a server level, FL regularly aggregates models learned locally on d…