62 citations · 118 across the 3 of their papers we have counts for
3 papers
cs.LG2021★ 17 cited
Self-supervised Cross-silo Federated Neural Architecture Search
Xinle Liang, Yang Liu, Jiahuan Luo +3
Federated Learning (FL) provides both model performance and data privacy for machine learning tasks where samples or features are distributed among different parties. In the traini…
cs.LG2020★ 62 cited
FedCVT: Semi-supervised Vertical Federated Learning with Cross-view Training
Yan Kang, Yang Liu, Xinle Liang
Federated learning allows multiple parties to build machine learning models collaboratively without exposing data. In particular, vertical federated learning (VFL) enables particip…
cs.LG2019★ 39 cited
Federated Transfer Reinforcement Learning for Autonomous Driving
Xinle Liang, Yang Liu, Tianjian Chen +2
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, uplo…