Self-supervised Cross-silo Federated Neural Architecture Search

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.

Neural Architecture Search Vertical Federated Learning

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

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.

Representation Learning Vertical Federated Learning

Federated Transfer Reinforcement Learning for Autonomous Driving

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.

Autonomous Driving Collision Avoidance +3