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01/01/2021
Mean-Field Game-Theoretic Edge Caching
In this book chapter, we study a problem of distributed content caching ...
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06/17/2020
Mix2FLD: Downlink Federated Learning After Uplink Federated Distillation With Two-Way Mixup
This letter proposes a novel communication-efficient and privacy-preserv...
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05/13/2020
Proxy Experience Replay: Federated Distillation for Distributed Reinforcement Learning
Traditional distributed deep reinforcement learning (RL) commonly relies...
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05/13/2020
Proxy Experience Replay: Federated Distillation for Distributed Reinforcement Leargning
Traditional distributed deep reinforcement learning (RL) commonly relies...
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08/16/2019
Distilling On-Device Intelligence at the Network Edge
Devices at the edge of wireless networks are the last mile data sources ...
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07/15/2019
Federated Reinforcement Distillation with Proxy Experience Memory
In distributed reinforcement learning, it is common to exchange the expe...
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07/15/2019
Multi-hop Federated Private Data Augmentation with Sample Compression
On-device machine learning (ML) has brought about the accessibility to a...
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11/28/2018
Communication-Efficient On-Device Machine Learning: Federated Distillation and Augmentation under Non-IID Private Data
On-device machine learning (ML) enables the training process to exploit ...
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08/12/2018
On-Device Federated Learning via Blockchain and its Latency Analysis
In this letter, we propose a block-chained federated learning (BlockFL) ...
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03/08/2018
Massive UAV-to-Ground Communication and its Stable Movement Control: A Mean-Field Approach
This paper proposes a real-time movement control algorithm for massive u...
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01/23/2018