This article investigates the use of deep learning to fairly distribute the tasks. An attention-based neural network model is proposed to generate efficient ...
Dec 7, 2021 · This article investigates the use of deep learning to fairly distribute the tasks. An attention-based neural network model is proposed to generate efficient ...
Semantic Scholar extracted view of "Attention-Based Model and Deep Reinforcement Learning for Distribution of Event Processing Tasks" by A. Mazayev et al.
Jun 23, 2022 · In this work we investigate how DRL can be used by reverse proxy servers to distribute event processing tasks among heterogeneous edge devices ...
Attention-based model and deep reinforcement learning for distribution of event processing tasks. A Mazayev, F Al-Tam, N Correia. Internet of Things 19, 100563, ...
Jun 17, 2024 · In this work, we propose a novel approach employing Deep Reinforcement Learning (DRL) methods to learn these heuristics for a specific multi-core architecture.
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Nov 15, 2024 · The attention mechanism allows the model to weight different parts of the input data, that is, assign different weights to different parts. In ...
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from publication: Attention-Based Model and Deep Reinforcement Learning for Distribution of Event Processing Tasks | Event processing is the cornerstone of ...
May 13, 2019 · In this paper, we present a novel attention-based deep reinforcement learning method in a multi-view environment in which each view can provide ...
Nov 28, 2023 · An attention mechanism is an Encoder-Decoder kind of neural network architecture that allows the model to focus on specific sections of the input while ...