Mohamad Assaad — accepted AI-conference papers

2023

Single Point-Based Distributed Zeroth-Order Optimization with a Non-Convex Stochastic Objective Function

ICML 2023poster

Zero-order (ZO) optimization is a powerful tool for dealing with realistic constraints. On the other hand, the gradient-tracking (GT) technique proved to be an efficient method for distributed optimization aiming to achieve consensus. However, it is a first-order (FO) method that requires knowledge…

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2019

Deep Learning Based Online Power Control for Large Energy Harvesting Networks

Mohit K. Sharma, Alessio Zappone, Mérouane Debbah, Mohamad Assaad

ICASSP 2019accepted

In this paper, we propose a deep learning based approach to design online power control policies for large EH networks, which are often intractable stochastic control problems. In the proposed approach, for a given EH network, the optimal on-line power control rule is learned by training a deep neur…

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