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

FedAWA: Aggregation Weight Adjustment in Federated Domain Generalization

Abstract: Domain Generalization (DG) in the setting of federated learning (i.e. Federated Domain Generalization, FDG) is gaining increasing attention. FDG aims to learn a global model generalizing ...
IEEE

3D point cloud robust sampling method based on aggregation rate

Abstract: Effective sampling plays a critical role in the preprocessing of 3D point cloud data, directly impacting the performance of downstream models. Traditional Farthest Point Sampling (FPS) ...
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

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

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

Optimizing Federated Learning With Aggregation Strategies: A Comprehensive Survey

Abstract: This article provides a comprehensive survey of aggregation strategies in federated learning (FL). This decentralized machine learning (ML) paradigm enables multiple clients to ...
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 ...