research
∙
12/15/2022
NAWQ-SR: A Hybrid-Precision NPU Engine for Efficient On-Device Super-Resolution
In recent years, image and video delivery systems have begun integrating...
share
research
∙
09/28/2021
Smart at what cost? Characterising Mobile Deep Neural Networks in the wild
With smartphones' omnipresence in people's pockets, Machine Learning (ML...
research
∙
04/20/2021
DynO: Dynamic Onloading of Deep Neural Networks from Cloud to Device
Recently, there has been an explosive growth of mobile and embedded appl...
research
∙
02/26/2021
FjORD: Fair and Accurate Federated Learning under heterogeneous targets with Ordered Dropout
Federated Learning (FL) has been gaining significant traction across dif...
research
∙
08/14/2020
SPINN: Synergistic Progressive Inference of Neural Networks over Device and Cloud
Despite the soaring use of convolutional neural networks (CNNs) in mobil...
research
∙
06/14/2019
Diffusing Your Mobile Apps: Extending In-Network Function Virtualization to Mobile Function Offloading
Motivated by the huge disparity between the limited battery capacity of ...
research
∙
05/17/2019
EmBench: Quantifying Performance Variations of Deep Neural Networks across Modern Commodity Devices
In recent years, advances in deep learning have resulted in unprecedente...
research
∙
03/09/2018
