Federated learning for energy constrained devices: a systematic mapping study

This publication has 52 references indexed in Scilit:

• Efficient Training Management for Mobile Crowd-Machine Learning: A Deep Reinforcement Learning Approach
  IEEE Wireless Communications Letters, 2019
• Privacy-Preserving Machine Learning: Threats and Solutions
  IEEE Security & Privacy, 2019
• Adaptive Federated Learning in Resource Constrained Edge Computing Systems
  IEEE Journal on Selected Areas in Communications, 2019
• Two-Stream Federated Learning: Reduce the Communication Costs
  2018
• Error-Controlled Lossy Compression Optimized for High Compression Ratios of Scientific Datasets
  2018
• A lightweight hybrid encryption technique to secure IoT data transmission
  International Journal of Engineering & Technology, 2018
• Short‐Range Cooperation of Mobile Devices for Energy‐Efficient Vertical Handovers
  Wireless Communications and Mobile Computing, 2018
• 5G D2D Networks: Techniques, Challenges, and Future Prospects
  IEEE Systems Journal, 2017
• The Power of Models: Modeling Power Consumption for IoT Devices
  IEEE Sensors Journal, 2015
• Double-bagging: combining classifiers by bootstrap aggregation
  Pattern Recognition, 2003