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09/25/2021
Motivating Learners in Multi-Orchestrator Mobile Edge Learning: A Stackelberg Game Approach
Mobile Edge Learning (MEL) is a learning paradigm that enables distribut...
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09/02/2021
Energy-Efficient Multi-Orchestrator Mobile Edge Learning
Mobile Edge Learning (MEL) is a collaborative learning paradigm that fea...
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11/30/2020
Task Allocation for Asynchronous Mobile Edge Learning with Delay and Energy Constraints
This paper extends the paradigm of "mobile edge learning (MEL)" by desig...
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06/12/2020
Returning the Favor: What Wireless Networking Can Offer to AI and Edge Learning
Machine learning (ML) and artificial intelligence (AI) have recently mad...
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06/12/2020
Optimal Task Allocation for Mobile Edge Learning with Global Training Time Constraints
This paper proposes to minimize the loss of training a distributed machi...
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05/05/2019
Adaptive Task Allocation for Asynchronous Federated Mobile Edge Learning
This paper proposes a scheme to efficiently execute distributed learning...
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11/09/2018
Adaptive Task Allocation for Mobile Edge Learning
This paper aims to establish a new optimization paradigm for implementin...
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06/20/2018
Throughput Maximization in Cloud-Radio Access Networks using Rate-Aware Network Coding
One of the most promising techniques for network-wide interference manag...
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01/16/2018
Throughput Maximization in Cloud Radio Access Networks using Network Coding
This paper is interested in maximizing the total throughput of cloud rad...
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12/09/2017
Deep Learning for IoT Big Data and Streaming Analytics: A Survey
In the era of the Internet of Things (IoT), an enormous amount of sensin...
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05/24/2017
