We make a case for in-network Continual Learning as a solution for seamless adaptation to evolving network conditions without forgetting past experiences. We propose implementing Active Learning-based selective data filtering in the data plane, allowing for data-efficient continual updates. We explore relevant challenges and propose future research directions.
Di Cicco N., Al Sadi A., Grasselli C., Melis A., Antichi G., Tornatore M. (2023). Poster: Continual Network Learning [10.1145/3603269.3610855].
Poster: Continual Network Learning
Al Sadi A.;Grasselli C.;Melis A.;
2023
Abstract
We make a case for in-network Continual Learning as a solution for seamless adaptation to evolving network conditions without forgetting past experiences. We propose implementing Active Learning-based selective data filtering in the data plane, allowing for data-efficient continual updates. We explore relevant challenges and propose future research directions.File in questo prodotto:
Eventuali allegati, non sono esposti
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
