We make a case for in-network Continual Learning as a solution for seamless adaptation to evolving network conditions without forgetting past experiences.

We make a case for in-network Continual Learning as a solution for seamless adaptation to evolving network conditions without forget- ting past experiences. We ...

Sep 10, 2023 · We make a case for in-network Continual Learning as a solution for seamless adaptation to evolving network conditions without forget- ting past ...

Poster: Continual Network Learning. paper ... Anonymized Internet Traces 2019. Dataset Icon. Anonymized Internet Traces 2018. C Copyright 2024 — Regents ...

Poster: Continual Network Learning. Cicco, N. D., Sadi, A. A., Grasselli, C., Melis, A., Antichi, G., & Tornatore, M. In Schulzrinne, H., Misra, V., Kohler ...

Request PDF | On Sep 10, 2023, Nicola Di Cicco and others published Poster: Continual Network Learning | Find, read and cite all the research you need on

In this paper, we study which modules in neural networks are more prone to forgetting by investigating their training dynamics during CL. Our proposed ...

We propose a novel framework and a solution to tackle the continual learning (CL) problem with changing network architectures.

Continual learning (CL) aims to train deep neural networks efficiently on streaming data while limiting the forgetting caused by new tasks. However, learning ...