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

Domain Generalization via Aggregation and Separation for Audio Deepfake Detection

Abstract: In this paper, we propose an Aggregation and Separation Domain Generalization (ASDG) method for Audio DeepFake Detection (ADD). Fake speech generated from different methods exhibits varied ...
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

Dual Aggregation Transformer for Image Super-Resolution

Abstract: Transformer has recently gained considerable popularity in low-level vision tasks, including image super-resolution (SR). These networks utilize self-attention along different dimensions, ...
IEEE

Multistage Particle Swarm Optimization for Heterogeneous Multipoint Dynamic Aggregation

Abstract: Multipoint dynamic aggregation (MPDA) is a multirobot task allocation problem, which requires the collaborative scheduling of multiple robots to complete time-varying tasks distributed on a ...
IEEE

Multi-stream Feature Aggregation Network for 3D Object Detection in Point Cloud

Abstract: In the recent 3D object detection methods for point clouds, the combination of point-based methods and voxel-based methods is gradually becoming a trend. Point-based methods retain the ...
IEEE

Explanatory Object Part Aggregation for Zero-Shot Learning

Abstract: Zero-shot learning (ZSL) aims to recognize objects from unseen classes only based on labeled images from seen classes. Most existing ZSL methods focus on optimizing feature spaces or ...
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

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

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

A Robust and Lightweight Privacy-Preserving Data Aggregation Scheme for Smart Grid

Abstract: Privacy-preserving data aggregation (PPDA) enables data availability and privacy preservation simultaneously in smart grid. However, existing methods, such ...