IEEE

Elastic Aggregation for Federated Optimization

Abstract: Federated learning enables the privacy-preserving training of neural network models using real-world data across distributed clients. FedAvg has become the preferred optimizer for federated ...
IEEE

A Flexible and Scalable Malicious Secure Aggregation Protocol for Federated Learning

Abstract: Secure aggregation becomes a major solution to providing privacy for federated learning. Secure aggregation for mobile devices typically relies on Shamir secret sharing (SSS) to achieve ...
IEEE

An Aggregation-Free Federated Learning for Tackling Data Heterogeneity

Abstract: The performance of Federated Learning (FL) hinges on the effectiveness of utilizing knowledge from distributed datasets. Traditional FL methods adopt an aggregate-then-adapt framework, where ...
IEEE

Joint Adaptive Aggregation and Resource Allocation for Hierarchical Federated Learning Systems Based on Edge-Cloud Collaboration

Abstract: Hierarchical federated learning shows excellent potential for communication-computation trade-offs and reliable data privacy protection by introducing edge-cloud collaboration. Considering ...
IEEE

Secure Aggregation in Heterogeneous Federated Learning for Digital Ecosystems

Abstract: Privacy-preserving federated learning (PPFL) is vital for Industry 5.0 digital ecosystems due to the increasing number of interconnected devices and the ...
IEEE

Host-driven In-Network Aggregation on RDMA

Abstract: Large-scale datacenter networks are increasingly using in-network aggregation (INA) and remote direct memory access (RDMA) techniques to accelerate deep neural network (DNN) training.
IEEE

A Lightweight Recurrent Aggregation Network for Satellite Video Super-Resolution

Abstract: Intelligent processing and analysis of satellite video has become one of the research hotspots in the representation of remote sensing, and satellite video super-resolution (SVSR) is an ...
IEEE

Cross-Modality Feature Aggregation for Cross-Domain Point Cloud Representation Learning

Abstract: Existing methods for learning 3D point cloud representation often use a single dataset-specific training and testing approach, leading to performance drops due to significant domain shifts ...
IEEE

DeepLA-Net: Very Deep Local Aggregation Networks for Point Cloud Analysis

Abstract: Due to the irregular and disordered data structure in 3D point clouds, prior works have focused on designing more sophisticated local representation methods to capture these complex local ...
IEEE

Fast Path Planning of Multienvironmental Factors Comprehensive Constraints in Off-Road Environment Constructed by Aggregation Vector Point Method

Abstract: The accuracy and efficiency of path planning in off-road environments depend on the construction of off-road environment map information. Previous studies have used the grid method to ...
IEEE

ELGC-Net: Efficient Local–Global Context Aggregation for Remote Sensing Change Detection

Abstract: Deep learning has shown remarkable success in remote sensing change detection (CD), aiming to identify semantic change regions between co-registered satellite image pairs acquired at ...