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Federated Imitation Learning: A Privacy Considered Imitation Learning
  Framework for Cloud Robotic Systems with Heterogeneous Sensor Data

Federated Imitation Learning: A Privacy Considered Imitation Learning Framework for Cloud Robotic Systems with Heterogeneous Sensor Data

3 September 2019
Boyi Liu
Lujia Wang
Ming Liu
Cheng-Zhong Xu
    FedML
ArXivPDFHTML

Papers citing "Federated Imitation Learning: A Privacy Considered Imitation Learning Framework for Cloud Robotic Systems with Heterogeneous Sensor Data"

3 / 3 papers shown
Title
Aggregating Capacity in FL through Successive Layer Training for
  Computationally-Constrained Devices
Aggregating Capacity in FL through Successive Layer Training for Computationally-Constrained Devices
Kilian Pfeiffer
R. Khalili
J. Henkel
FedML
55
5
0
26 May 2023
Deep Federated Learning for Autonomous Driving
Deep Federated Learning for Autonomous Driving
A. Nguyen
Tuong Khanh Long Do
Minh-Ngoc Tran
Binh X. Nguyen
C. Duong
T. Phan
Erman Tjiputra
Quang-Dieu Tran
FedML
36
109
0
12 Oct 2021
A Survey on Federated Learning and its Applications for Accelerating
  Industrial Internet of Things
A Survey on Federated Learning and its Applications for Accelerating Industrial Internet of Things
Jiehan Zhou
Shouhua Zhang
Qinghua Lu
W. Dai
Min Chen
Xin Liu
Susanna Pirttikangas
Yang Shi
Weishan Zhang
E. Herrera-Viedma
FedML
AI4CE
28
44
0
21 Apr 2021
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