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A Machine Learning Approach for Task and Resource Allocation in Mobile Edge Computing Based Networks
Since the data size of each computational task is different, as the requested computational task varies, the BSs must adjust their resource (subcarrier and transmit power) and task allocation schemes to effectively serve the users.
Analysis of Memory Capacity for Deep Echo State Networks
Then, a series architecture ESN is proposed in which ESN reservoirs are placed in cascade that the output of each ESN is the input of the next ESN in the series.
Federated Echo State Learning for Minimizing Breaks in Presence in Wireless Virtual Reality Networks
The proposed algorithm uses concept from federated learning to enable multiple BSs to locally train their deep ESNs using their collected data and cooperatively build a learning model to predict the entire users' locations and orientations.
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