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08/04/2023
Universal Approximation of Linear Time-Invariant (LTI) Systems through RNNs: Power of Randomness in Reservoir Computing
Recurrent neural networks (RNNs) are known to be universal approximators...
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03/02/2023
Distributed Learning Meets 6G: A Communication and Computing Perspective
With the ever-improving computing capabilities and storage capacities of...
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06/28/2021
Federated Dynamic Spectrum Access
Due to the growing volume of data traffic produced by the surge of Inter...
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12/01/2020
Learning with Knowledge of Structure: A Neural Network-Based Approach for MIMO-OFDM Detection
In this paper, we explore neural network-based strategies for performing...
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11/10/2020
Learning for Integer-Constrained Optimization through Neural Networks with Limited Training
In this paper, we investigate a neural network-based learning approach t...
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07/15/2020
Federated Learning in Mobile Edge Computing: An Edge-Learning Perspective for Beyond 5G
Owing to the large volume of sensed data from the enormous number of IoT...
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03/15/2020