2 papers
cs.LG2022
Adaptive Differential Filters for Fast and Communication-Efficient Federated Learning
Daniel Becking, Heiner Kirchhoffer, Gerhard Tech +4
Federated learning (FL) scenarios inherently generate a large communication overhead by frequently transmitting neural network updates between clients and server. To minimize the c…
cs.AR2020
FantastIC4: A Hardware-Software Co-Design Approach for Efficiently Running 4bit-Compact Multilayer Perceptrons
Simon Wiedemann, Suhas Shivapakash, Pablo Wiedemann +4
With the growing demand for deploying deep learning models to the "edge", it is paramount to develop techniques that allow to execute state-of-the-art models within very tight and…