Aug 8, 2022 · We propose a novel and adaptive feature space distillation method (AFSD) to reduce the communication overhead among distributed computers.
scholar.google.com › citations
The proposed method improves the Codistillation process by supporting longer update interval rates. AFSD performs knowledge distillates across the models.
We propose a novel and adaptive feature space distillation method (AFSD) to reduce the communication overhead among distributed computers.
A novel and adaptive feature space distillation method (AFSD) to reduce the communication overhead among distributed computers and improves the ...
AFSD: Adaptive Feature Space Distillation for Distributed Deep Learning. S Khaleghian, H Ullah, EB Johnsen, A Andersen, A Marinoni. IEEE Access 10, 84569 ...
We propose a novel and adaptive feature space distillation method (AFSD) to reduce the communication overhead among distributed computers.
We propose a novel and adaptive feature space distillation method (AFSD) to reduce the communication overhead among distributed computers.
AFSD: Adaptive Feature Space Distillation for Distributed Deep Learning. Request PDF. Open Access. IEEE Access. Profile Image. Salman Khaleghian · Profile Image.
AFSD: Adaptive Feature Space Distillation for Distributed Deep Learning · Artificial intelligence and big data technologies for copernicus data: the extremeearth ...
Apr 25, 2024 · AFSD: Adaptive Feature Space Distillation for Distributed Deep Learning. ... A Noise-Aware Deep Learning Model for Sea Ice Classification ...