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20 hours ago · [20] proposed asynchronous federated learning, where deep reinforcement learning (DRL) on the server selects nodes with higher communica- tion and computation ...
5 days ago · The paper studies a fundamental federated learning (FL) problem involving multiple clients with heterogeneous constrained resources.
2 days ago · The first approach constructs a training pipeline to balance the overall training workload by (a) reallocating the computations for different DNN layers on the ...
7 days ago · SLAs-aware online task scheduling based on deep reinforcement learning method in cloud environment. In: 2019 IEEE 21st International Conference on High.
3 days ago · We propose a hierarchical approach by decomposing the formulated problem into two sub-problems and combining ant colony optimization (ACO) algorithm [14] and ...
24 hours ago · [13] proposed a MEC framework supporting D2D to minimize the latency of computation offloading. The offloading cost is influenced by the distance between users ...
3 days ago · ... students up to grade level work and beyond. While online learning apps offer extensive educational resources, students often underutilize them due to lower.
2 days ago · Our goal in this paper is to reduce the communication cost in decentralized learning for any data distribution without hurting convergence. Report issue for ...
2 days ago · Then, we formulate the joint optimization problem of computation offloading, resource allocation and charging scheduling as a Markov Decision Process (MDP), and ...
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