Yan Kang

According to our database, Yan Kang authored at least 27 papers between 2019 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

FedEval-LLM: Federated Evaluation of Large Language Models on Downstream Tasks with Collective Wisdom.

Yuanqin He, Yan Kang, Lixin Fan, Qiang Yang

CoRR, 2024

Hyperparameter Optimization for SecureBoost via Constrained Multi-Objective Federated Learning.

Yan Kang, Ziyao Ren, Lixin Fan, Linghua Yang, Yongxin Tong, Qiang Yang

CoRR, 2024

SecureBoost+: Large Scale and High-Performance Vertical Federated Gradient Boosting Decision Tree.

Tao Fan, Weijing Chen, Guoqiang Ma, Yan Kang, Lixin Fan, Qiang Yang

Proceedings of the Advances in Knowledge Discovery and Data Mining, 2024

2023

Trading Off Privacy, Utility, and Efficiency in Federated Learning.

Xiaojin Zhang, Yan Kang, Kai Chen, Lixin Fan, Qiang Yang

ACM Trans. Intell. Syst. Technol., December, 2023

A Theoretical Analysis of Efficiency Constrained Utility-Privacy Bi-Objective Optimization in Federated Learning.

Hanlin Gu, Xinyuan Zhao, Yuxing Han, Yan Kang, Lixin Fan, Qiang Yang

CoRR, 2023

Grounding Foundation Models through Federated Transfer Learning: A General Framework.

Yan Kang, Tao Fan, Hanlin Gu, Lixin Fan, Qiang Yang

CoRR, 2023

FATE-LLM: A Industrial Grade Federated Learning Framework for Large Language Models.

Tao Fan, Yan Kang, Guoqiang Ma, Weijing Chen, Wenbin Wei, Lixin Fan, Qiang Yang

CoRR, 2023

SecureBoost Hyperparameter Tuning via Multi-Objective Federated Learning.

Ziyao Ren, Yan Kang, Lixin Fan, Linghua Yang, Tao Fan, Yongxin Tong, Qiang Yang

CoRR, 2023

A Meta-learning Framework for Tuning Parameters of Protection Mechanisms in Trustworthy Federated Learning.

Xiaojin Zhang, Yan Kang, Lixin Fan, Kai Chen, Qiang Yang

CoRR, 2023

Optimizing Privacy, Utility and Efficiency in Constrained Multi-Objective Federated Learning.

Yan Kang, Hanlin Gu, Xingxing Tang, Yuanqin He, Yuzhu Zhang, Jinnan He, Yuxing Han, Lixin Fan, Kai Chen, Qiang Yang

CoRR, 2023

FedPass: Privacy-Preserving Vertical Federated Deep Learning with Adaptive Obfuscation.

Hanlin Gu, Jiahuan Luo, Yan Kang, Lixin Fan, Qiang Yang

Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023

2022

FedBCD: A Communication-Efficient Collaborative Learning Framework for Distributed Features.

Yang Liu, Xinwei Zhang, Yan Kang, Liping Li, Tianjian Chen, Mingyi Hong, Qiang Yang

IEEE Trans. Signal Process., 2022

FedCVT: Semi-supervised Vertical Federated Learning with Cross-view Training.

Yan Kang, Yang Liu, Xinle Liang

ACM Trans. Intell. Syst. Technol., 2022

Vertical Federated Learning.

Yang Liu, Yan Kang, Tianyuan Zou, Yanhong Pu, Yuanqin He, Xiaozhou Ye, Ye Ouyang, Ya-Qin Zhang, Qiang Yang

CoRR, 2022

A Framework for Evaluating Privacy-Utility Trade-off in Vertical Federated Learning.

Yan Kang, Jiahuan Luo, Yuanqin He, Xiaojin Zhang, Lixin Fan, Qiang Yang

CoRR, 2022

A Hybrid Self-Supervised Learning Framework for Vertical Federated Learning.

Yuanqin He, Yan Kang, Jiahuan Luo, Lixin Fan, Qiang Yang

CoRR, 2022

Accelerating Vertical Federated Learning.

Dongqi Cai, Tao Fan, Yan Kang, Lixin Fan, Mengwei Xu, Shangguang Wang, Qiang Yang

CoRR, 2022

FedCG: Leverage Conditional GAN for Protecting Privacy and Maintaining Competitive Performance in Federated Learning.

Yuezhou Wu, Yan Kang, Jiahuan Luo, Yuanqin He, Lixin Fan, Rong Pan, Qiang Yang

Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022

2021

Defending Label Inference and Backdoor Attacks in Vertical Federated Learning.

Yang Liu, Zhihao Yi, Yan Kang, Yuanqin He, Wenhan Liu, Tianyuan Zou, Qiang Yang

CoRR, 2021

Privacy-preserving Federated Adversarial Domain Adaption over Feature Groups for Interpretability.

Yan Kang, Yang Liu, Yuezhou Wu, Guoqiang Ma, Qiang Yang

CoRR, 2021

FedCG: Leverage Conditional GAN for Protecting Privacy and Maintaining Competitive Performance in Federated Learning.

Yuezhou Wu, Yan Kang, Jiahuan Luo, Yuanqin He, Qiang Yang

CoRR, 2021

SecureBoost+ : A High Performance Gradient Boosting Tree Framework for Large Scale Vertical Federated Learning.

Weijing Chen, Guoqiang Ma, Tao Fan, Yan Kang, Qian Xu, Qiang Yang

CoRR, 2021

Federated Deep Learning with Bayesian Privacy.

Hanlin Gu, Lixin Fan, Bowen Li, Yan Kang, Yuan Yao, Qiang Yang

CoRR, 2021

2020

A Secure Federated Transfer Learning Framework.

Yang Liu, Yan Kang, Chaoping Xing, Tianjian Chen, Qiang Yang

IEEE Intell. Syst., 2020

FedML: A Research Library and Benchmark for Federated Machine Learning.

Chaoyang He, Songze Li, Jinhyun So, Mi Zhang, Hongyi Wang, Xiaoyang Wang, Praneeth Vepakomma, Abhishek Singh, Hang Qiu, Li Shen, Peilin Zhao, Yan Kang, Yang Liu, Ramesh Raskar, Qiang Yang, Murali Annavaram, Salman Avestimehr

CoRR, 2020

2019

Federated Learning

Qiang Yang, Yang Liu, Yong Cheng, Yan Kang, Tianjian Chen, Han Yu

Synthesis Lectures on Artificial Intelligence and Machine Learning, Morgan & Claypool Publishers, ISBN: 978-3-031-01585-4, 2019

A Communication Efficient Vertical Federated Learning Framework.

Yang Liu, Yan Kang, Xinwei Zhang, Liping Li, Yong Cheng, Tianjian Chen, Mingyi Hong, Qiang Yang

CoRR, 2019