Wei–Neng Chen

When Crowdsensing Meets Federated Learning: Privacy-Preserving Mobile Crowdsensing System

2021 · arXiv (Cornell University)

Mobile crowdsensing (MCS) is an emerging sensing data collection pattern with scalability, low deployment cost, and distributed characteristics. Traditional MCS systems suffer from privacy concerns and fair reward distribution. Moreover, existing privacy-preserving MCS solutions usually …

EvoS&R: Evolving Multiple Seeds and Radii for Varying Density Data Clustering

2023 · IEEE Transactions on Knowledge and Data Engineering

Density clustering has shown advantages over other types of clustering methods for processing arbitrarily shaped datasets. In recent years, extensive research efforts has been made on the improvements of DBSCAN or the algorithms incorporating the …

Multiagent Swarm Optimization With Adaptive Internal and External Learning for Complex Consensus-Based Distributed Optimization

2024 · IEEE Transactions on Evolutionary Computation

Distributed optimization has attracted lots of attention in recent years. Thanks to the intrinsic parallelism and great search capacity, evolutionary computation (EC) has the potential for black-box and non-convex distributed optimization. However, due to the …