Yan Kang

发表

Federated Learning

Yang Liu, Qiang Yang, Han Yu, 2019, Synthesis Lectures on Artificial Intelligence and Machine Learning.

A Communication Efficient Vertical Federated Learning Framework

Qiang Yang, Yang Liu, Mingyi Hong, 2019, ArXiv.

Federated Deep Learning with Bayesian Privacy pdf

Qiang Yang, Yan Kang, Lixin Fan, 2021, ArXiv.

Bridging the Gap between Data Integration and ML Systems

Yan Kang, A. Ionescu, Rihan Hai, 2022, ArXiv.

Accelerating Vertical Federated Learning

Yan Kang, Dongqi Cai, Mengwei Xu, 2022, IEEE Transactions on Big Data.

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

Yan Kang, Lixin Fan, Jiahuan Luo, 2022, 2209.03885.

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

Qiang Yang, Yan Kang, Jiahuan Luo, 2021, IJCAI.

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

Yan Kang, Lixin Fan, Jiahuan Luo, 2022, ArXiv.

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

Yang Liu, Yan Kang, Xinle Liang, 2020, ACM Trans. Intell. Syst. Technol..

Trading Off Privacy, Utility and Efficiency in Federated Learning

Yan Kang, Lixin Fan, Kai Chen, 2022, 2209.00230.

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

Qiang Yang, Yang Liu, Yan Kang, 2021, IEEE Transactions on Big Data.

Amalur: Data Integration Meets Machine Learning

Yan Kang, Rihan Hai, Christos Koutras, 2022, 2205.09681.

Vertical Federated Learning

Yang Liu, Yan Kang, Tianyuan Zou, 2022, ArXiv.

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

Ramesh Raskar, Yang Liu, Xiaoyang Wang, 2020, ArXiv.

A Secure Federated Transfer Learning Framework

Tianjian Chen, Yan Kang, Chaoping Xing, 2020, IEEE Intelligent Systems.

A Communication Efficient Collaborative Learning Framework for Distributed Features

Yang Liu, Qiang Yang, Mingyi Hong, 2019 .

Secure and Efficient Federated Transfer Learning

Chaoping Xing, Yan Kang, Yang Liu, 2019, 2019 IEEE International Conference on Big Data (Big Data).

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

Yan Kang, Hanlin Gu, Lixin Fan, 2023, ArXiv.

Amalur: Data Integration Meets Machine Learning

Yan Kang, Rihan Hai, Christos Koutras, 2022, 2023 IEEE 39th International Conference on Data Engineering (ICDE).

Defending Batch-Level Label Inference and Replacement Attacks in Vertical Federated Learning

Yang Liu, Yan Kang, Qian Yang, 2022, IEEE Transactions on Big Data.

Batch Label Inference and Replacement Attacks in Black-Boxed Vertical Federated Learning

Yang Liu, Yan Kang, Tianyuan Zou, 2021, 2112.05409.

A novel approach to simultaneously improve privacy, efficiency and reliability of federated DNN learning

Qiang Yang, Yan Kang, Hanlin Gu, 2021 .

Defending Label Inference and Backdoor Attacks in Vertical Federated Learning pdf

Yang Liu, Yan Kang, Tianyuan Zou, 2021, ArXiv.

Federated Learning

Yang Liu, Qiang Yang, Han Yu, 2019, Synthesis Lectures on Artificial Intelligence and Machine Learning.

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

Yan Kang, Hanlin Gu, Lixin Fan, 2023, IJCAI.

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

Yan Kang, Lixin Fan, Kai Chen, 2023, ArXiv.

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

Qiang Yang, Qian Xu, Yan Kang, 2021, ArXiv.

FedML: A Research Library and Benchmark for Federated Machine Learning

Hongyi Wang, R. Raskar, M. Annavaram, 2020, ArXiv.

A Hybrid Self-Supervised Learning Framework for Vertical Federated Learning

Yan Kang, Lixin Fan, Jiahuan Luo, 2022, ArXiv.

Grounding Foundation Models through Federated Transfer Learning: A General Framework

Yan Kang, Tao Fan, Hanlin Gu, 2023, ArXiv.

Vertical Federated Learning: Concepts, Advances, and Challenges

Yang Liu, Yan Kang, Tianyuan Zou, 2022, IEEE Transactions on Knowledge and Data Engineering.

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

Yan Kang, Tao Fan, Lixin Fan, 2023, ArXiv.

FedMVT: Semi-supervised Vertical Federated Learning with MultiView Training pdf

Tianjian Chen, Yang Liu, Yan Kang, 2020, ArXiv.