42 citations · 43 across the 5 of their papers we have counts for
5 papers
Information Elicitation from Decentralized Crowd Without Verification
Kexin Chen, Chao Huang, Jianwei Huang
Information Elicitation Without Verification (IEWV) refers to the problem of eliciting high-accuracy solutions from crowd members when the ground truth is unverifiable. A high-accu…
Federated Learning in Competitive EV Charging Market
Chenxi Sun, Chao Huang, Biying Shou +1
Federated Learning (FL) has demonstrated a significant potential to improve the quality of service (QoS) of EV charging stations. While existing studies have primarily focused on d…
Incentive Mechanism Design for Distributed Ensemble Learning
Chao Huang, Pengchao Han, Jianwei Huang
Distributed ensemble learning (DEL) involves training multiple models at distributed learners, and then combining their predictions to improve performance. Existing related studies…
Cross-Silo Federated Learning: Challenges and Opportunities
Chao Huang, Jianwei Huang, Xin Liu
Federated learning (FL) is an emerging technology that enables the training of machine learning models from multiple clients while keeping the data distributed and private. Based o…
Strategic Information Revelation in Crowdsourcing Systems Without Verification
Chao Huang, Haoran Yu, Jianwei Huang +1
We study a crowdsourcing problem where the platform aims to incentivize distributed workers to provide high quality and truthful solutions without the ability to verify the solutio…