Postdoctoral researcher

Chao Huang

Postdoctoral Researcher

AIFS publications

About Chao

Chao is a Postdoctoral Researcher for AIFS.

14 publications

AIFS publications

Journal Article · Machine Learning · 2025
An Empirical Study on Impact of Label Noise on Synthetic Tabular Data Generation
Kim, Jeonghoon, Chao Huang, and Xin Liu
Paper page for An empirical study on impact of label noise on synthetic tabular data generation PDF of An empirical study on impact of label noise on synthetic tabular data generation DOI 10.1007/s10994-024-06629-5
Conference Article · Advances in Neural Information Processing Systems 37 · 2024
Convergence Analysis of Split Federated Learning on Heterogeneous Data
Han, Pengchao, Chao Huang, Geng Tian, Ming Tang, and Xin Liu
Paper page for Convergence Analysis of Split Federated Learning on Heterogeneous Data PDF of Convergence Analysis of Split Federated Learning on Heterogeneous Data DOI 10.52202/079017-3287
Conference Article · Lecture Notes in Computer Science · 2024
An Accuracy-Shaping Mechanism for Competitive Distributed Learning
Huang, Chao, Justin Dachille, and Xin Liu
Paper page for An Accuracy-Shaping Mechanism for Competitive Distributed Learning DOI 10.1007/978-3-031-72347-6_10
Conference Article · Computer Vision and Pattern Recognition · 2024
Feduv: Uniformity and Variance for Heterogeneous Federated Learning
Son, Ha M, Moon-Hyun Kim, Tai-Myoung Chung, Chao Huang, and Xin Liu
Paper page for Feduv: uniformity and variance for heterogeneous federated learning Project for Feduv: uniformity and variance for heterogeneous federated learning DOI 10.1109/CVPR52733.2024.00560
Journal Article · IEEE Internet of Things Journal · 2024
When Federated Learning Meets Oligopoly Competition: Stability and Model Differentiation
Huang, Chao, Justin Dachille, and Xin Liu
Paper page for When Federated Learning Meets Oligopoly Competition: Stability and Model Differentiation DOI 10.1109/JIOT.2024.3400216
Journal Article · IEEE communications magazine · 2023
Promoting Collaboration in Cross-Silo Federated Learning: Challenges and Opportunities
Huang, Chao, Ming Tang, Qian Ma, Jianwei Huang, and Xin Liu
Paper page for Promoting Collaboration in Cross-Silo Federated Learning: Challenges and Opportunities DOI 10.1109/MCOM.005.2300467
Journal Article · Scientific Reports · 2023
Infection Prediction in Swine Populations with Machine Learning
Halev, Avishai, Beatriz Martínez-López, Maria Clavijo, Carlos Gonzalez-Crespo, Jeonghoon Kim, Chao Huang, Seth Krantz, Rebecca Robbins, and Xin Liu
Paper page for Infection prediction in swine populations with machine learning PDF of Infection prediction in swine populations with machine learning DOI 10.1038/s41598-023-43472-5
Conference Article · 2023 21st International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks (WiOpt) · 2023
On the Impact of Label Noise in Federated Learning
Ke, Shuqi, Chao Huang, and Xin Liu
Paper page for On the Impact of Label Noise in Federated Learning DOI 10.23919/wiopt58741.2023.10349830
Workshop Article · 2023 21st International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks (WiOpt) · 2023
On the Impact of Label Noise in Federated Learning
Ke, Shuqi, Chao Huang, and Xin Liu
Paper page for On the Impact of Label Noise in Federated Learning Project for On the Impact of Label Noise in Federated Learning DOI 10.23919/wiopt58741.2023.10349830
Journal Article · IEEE Transactions on Network Science and Engineering · 2023
Duopoly Business Competition in Cross-Silo Federated Learning
Huang, Chao, Shuqi Ke, and Xin Liu
DOI 10.1109/TNSE.2023.3297880
Journal Article · Frontiers in Microbiology · 2023
Predicting Antimicrobial Resistance of Bacterial Pathogens Using Time Series Analysis
Kim, Jeonghoon, Ruwini Rupasinghe, Avishai Halev, Chao Huang, Shahbaz Rezaei, Maria Clavijo, Rebecca Robbins, Beatriz Martínez-López, and Xin Liu
Paper page for Predicting antimicrobial resistance of bacterial pathogens using time series analysis PDF of Predicting antimicrobial resistance of bacterial pathogens using time series analysis DOI 10.3389/fmicb.2023.1160224
Preprint · Research Square · 2023
Outbreak Prediction in Swine Populations with Machine Learning
Halev, Avishai, Beatriz Martínez-López, Maria Clavijo, Carlos Gonzalez-Crespo, Jeonghoon Kim, Chao Huang, Rebecca Robbins, and Xin Liu
Paper page for Outbreak Prediction in Swine Populations with Machine Learning PDF of Outbreak Prediction in Swine Populations with Machine Learning DOI 10.21203/rs.3.rs-2814859/v1
Preprint · arXiv · 2022
Cross-Silo Federated Learning: Challenges and Opportunities
Huang, Chao, Jianwei Huang, and Xin Liu
Paper page for Cross-Silo Federated Learning: Challenges and Opportunities PDF of Cross-Silo Federated Learning: Challenges and Opportunities Project for Cross-Silo Federated Learning: Challenges and Opportunities DOI 10.48550/arxiv.2206.12949
Preprint · arXiv · 2022
Incentivizing Data Contribution in Cross-Silo Federated Learning
Huang, Chao, Shuqi Ke, Charles Kamhoua, Prasant Mohapatra, and Xin Liu
Paper page for Incentivizing Data Contribution in Cross-Silo Federated Learning PDF of Incentivizing Data Contribution in Cross-Silo Federated Learning Project for Incentivizing Data Contribution in Cross-Silo Federated Learning DOI 10.48550/arxiv.2203.03885

Back to the team

Chao Huang

AIFS publications

An Empirical Study on Impact of Label Noise on Synthetic Tabular Data Generation

Convergence Analysis of Split Federated Learning on Heterogeneous Data

An Accuracy-Shaping Mechanism for Competitive Distributed Learning

Feduv: Uniformity and Variance for Heterogeneous Federated Learning

When Federated Learning Meets Oligopoly Competition: Stability and Model Differentiation

Promoting Collaboration in Cross-Silo Federated Learning: Challenges and Opportunities

Infection Prediction in Swine Populations with Machine Learning

On the Impact of Label Noise in Federated Learning

On the Impact of Label Noise in Federated Learning

Duopoly Business Competition in Cross-Silo Federated Learning

Predicting Antimicrobial Resistance of Bacterial Pathogens Using Time Series Analysis

Outbreak Prediction in Swine Populations with Machine Learning

Cross-Silo Federated Learning: Challenges and Opportunities

Incentivizing Data Contribution in Cross-Silo Federated Learning