IoT Device Friendly and Communication-Efficient Federated Learning via Joint Model Pruning and Quantization
Sign Up to like & getrecommendations! 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… read more here.
Keywords: communication; federated learning; quantization; model pruning ... See more keywords
NestFL: Enhancing Federated Learning Through Nested Multicapacity Model Pruning in Heterogeneous Edge Computing
Sign Up to like & getrecommendations! Published in 2024 at "IEEE Internet of Things Journal"
DOI: 10.1109/jiot.2025.3562633
Abstract: Federated learning (FL) has emerged as a pivotal approach for edge-based distributed machine learning, yet it faces significant challenges due to the constrained capacities and heterogeneity of edge devices, including non-IID data distribution, communication constraints,… read more here.
Keywords: nestfl enhancing; edge; edge computing; model pruning ... See more keywords
Model Pruning Enables Efficient Federated Learning on Edge Devices
Sign Up to like & getrecommendations! 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… read more here.
Keywords: model pruning; federated learning; model; original model ... See more keywords
Model Pruning for Distributed Learning Over the Air
Sign Up to like & getrecommendations! Published in 2024 at "IEEE Transactions on Signal Processing"
DOI: 10.1109/tsp.2024.3486169
Abstract: Analog over-the-air (A-OTA) computing is an effective approach to achieving distributed learning among multiple end-user devices within a bandwidth-constrained spectrum. In this paradigm, users’ intermediate parameters, such as gradients, are modulated onto a set of… read more here.
Keywords: pruning distributed; distributed learning; model pruning; learning air ... See more keywords
Adaptive Model Pruning for Communication and Computation Efficient Wireless Federated Learning
Sign Up to like & getrecommendations! Published in 2024 at "IEEE Transactions on Wireless Communications"
DOI: 10.1109/twc.2023.3342626
Abstract: Most existing wireless federated learning (FL) studies focused on homogeneous model settings where devices train identical local models. In this setting, the devices with poor communication and computation capabilities may delay the global model update… read more here.
Keywords: communication computation; model pruning; wireless federated; model ... See more keywords
Model pruning based on filter similarity for edge device deployment
Sign Up to like & getrecommendations! 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… read more here.
Keywords: similarity; pruning based; model pruning; based filter ... See more keywords
Kinematic Model Pruning: A Design Optimization Technique for Simultaneous Optimization of Topology and Geometry
Sign Up to like & getrecommendations! 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… read more here.
Keywords: topology; design optimization; model pruning; geometry ... See more keywords