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Published in 2022 at "IEEE Internet of Things Journal"
DOI: 10.1109/jiot.2022.3145865
Abstract: Federated learning (FL) through its novel applications and services has enhanced its presence as a promising tool in the Internet of Things (IoT) domain. Specifically, in a multiaccess edge computing setup with a host of…
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Keywords:
communication;
federated learning;
quantization;
model pruning ... See more keywords
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Published in 2022 at "IEEE transactions on neural networks and learning systems"
DOI: 10.1109/tnnls.2022.3166101
Abstract: Federated learning (FL) allows model training from local data collected by edge/mobile devices while preserving data privacy, which has wide applicability to image and vision applications. A challenge is that client devices in FL usually…
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Keywords:
model pruning;
federated learning;
model;
original model ... See more keywords
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1
Published in 2023 at "Frontiers in Neurorobotics"
DOI: 10.3389/fnbot.2023.1132679
Abstract: Filter pruning is widely used for inference acceleration and compatibility with off-the-shelf hardware devices. Some filter pruning methods have proposed various criteria to approximate the importance of filters, and then sort the filters globally or…
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Keywords:
similarity;
pruning based;
model pruning;
based filter ... See more keywords
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Published in 2022 at "Robotics"
DOI: 10.3390/robotics11020031
Abstract: This paper presents a method of optimizing the design of robotic manipulators using a novel kinematic model pruning technique. The optimization departs from an predefined candidate linkage consisting of a initial topology and geometry. It…
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Keywords:
topology;
design optimization;
model pruning;
geometry ... See more keywords