no code implementations • 28 Jan 2021 • Xinle Liang, Yang Liu, Jiahuan Luo, Yuanqin He, Tianjian Chen, Qiang Yang
Federated Learning (FL) provides both model performance and data privacy for machine learning tasks where samples or features are distributed among different parties.
no code implementations • 25 Aug 2020 • Yan Kang, Yang Liu, Xinle Liang
In this article, we propose Federated Cross-view Training (FedCVT), a semi-supervised learning approach that improves the performance of the VFL model with limited aligned samples.
no code implementations • 14 Oct 2019 • Xinle Liang, Yang Liu, Tianjian Chen, Ming Liu, Qiang Yang
Reinforcement learning (RL) is widely used in autonomous driving tasks and training RL models typically involves in a multi-step process: pre-training RL models on simulators, uploading the pre-trained model to real-life robots, and fine-tuning the weight parameters on robot vehicles.