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20192024
most citedNovel Suboptimal approaches for Hyperparameter Tuning of Deep Neural Network [under the shelf of Optical Communication]

3 citations · 5 across the 4 of their papers we have counts for

collaborators

5 papers

eess.SP20242 cited

A Survey on Machine and Deep Learning for Optical Communications

M. A. Amirabadi, S. A. Nezamalhosseini, M. H. Kahaei +1

The ever-growing complexity of optical communication systems and networks demands sophisticated methodologies to extract meaningful insights from vast amounts of heterogeneous data…

eess.SP2021

Joint Power and Gain Allocation in MDM-WDM Optical Communication Networks Based on Enhanced Gaussian Noise Model

Mohammad Ali Amirabadi, Mohammad Hossein Kahaei, S. Alireza Nezamalhosseini

Achieving reliable communication over different channels and modes is one of the main goals of Mode Division Multiplexing-Wavelength Division Multiplexing (MDM-WDM) communication n…

cs.IT2020

Resource Allocation of Dual-Hop VLC/RF Systems with Light Energy Harvesting

Shayan Zargari, Mehrdad Kolivand, S. Alireza Nezamalhosseini +3

In this paper, we study the time allocation optimization problem to maximize the sum throughput in a dual-hop heterogeneous visible light communication (VLC)/radio frequency (RF) c…

eess.SP2019

Deep learning for channel estimation in FSO communication system

M. A. Amirabadi

Perfect channel estimation is very hard, time/ power consuming, and expensive; so it is not preferred (e.g. in mobile) communication systems. This paper seeks for new, cheap, low c…

eess.SP20193 cited

Novel Suboptimal approaches for Hyperparameter Tuning of Deep Neural Network [under the shelf of Optical Communication]

M. A. Amirabadi

Hyperparameter tuning is the main challenge of machine learning (ML) algorithms. Grid search is a popular method in hyperparameter tuning of simple ML algorithms; however, high com…