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08/21/2023
A Safe Deep Reinforcement Learning Approach for Energy Efficient Federated Learning in Wireless Communication Networks
Progressing towards a new era of Artificial Intelligence (AI) - enabled ...
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07/18/2023
Federated Learning for Computationally-Constrained Heterogeneous Devices: A Survey
With an increasing number of smart devices like internet of things (IoT)...
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06/25/2023
A Safe Genetic Algorithm Approach for Energy Efficient Federated Learning in Wireless Communication Networks
Federated Learning (FL) has emerged as a decentralized technique, where ...
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05/26/2023
Aggregating Capacity in FL through Successive Layer Training for Computationally-Constrained Devices
Federated learning (FL) is usually performed on resource-constrained edg...
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05/24/2023
FedZero: Leveraging Renewable Excess Energy in Federated Learning
Federated Learning (FL) is an emerging machine learning technique that e...
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07/29/2022
Multi-Agent Reinforcement Learning for Long-Term Network Resource Allocation through Auction: a V2X Application
We formulate offloading of computational tasks from a dynamic group of m...
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07/13/2022
Scheduling Out-of-Coverage Vehicular Communications Using Reinforcement Learning
Performance of vehicle-to-vehicle (V2V) communications depends highly on...
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04/05/2022
Learning to Bid Long-Term: Multi-Agent Reinforcement Learning with Long-Term and Sparse Reward in Repeated Auction Games
We propose a multi-agent distributed reinforcement learning algorithm th...
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04/05/2022
Multi-Agent Distributed Reinforcement Learning for Making Decentralized Offloading Decisions
We formulate computation offloading as a decentralized decision-making p...
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03/10/2022
CoCo-FL: Communication- and Computation-Aware Federated Learning via Partial NN Freezing and Quantization
Devices participating in federated learning (FL) typically have heteroge...
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12/16/2021
DISTREAL: Distributed Resource-Aware Learning in Heterogeneous Systems
We study the problem of distributed training of neural networks (NNs) on...
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06/09/2020
Distributed Learning on Heterogeneous Resource-Constrained Devices
We consider a distributed system, consisting of a heterogeneous set of d...
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07/22/2019
VRLS: A Unified Reinforcement Learning Scheduler for Vehicle-to-Vehicle Communications
Vehicle-to-vehicle (V2V) communications have distinct challenges that ne...
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04/29/2019
