52 citations · 100 across the 20 of their papers we have counts for
6 papers · 1 filter
Efficient power allocation using graph neural networks and deep algorithm unfolding
Arindam Chowdhury, Gunjan Verma, Chirag Rao +2
We study the problem of optimal power allocation in a single-hop ad hoc wireless network. In solving this problem, we propose a hybrid neural architecture inspired by the algorithm…
Adaptive Contention Window Design using Deep Q-learning
Abhishek Kumar, Gunjan Verma, Chirag Rao +2
We study the problem of adaptive contention window (CW) design for random-access wireless networks. More precisely, our goal is to design an intelligent node that can dynamically a…
Distributed Scheduling using Graph Neural Networks
Zhongyuan Zhao, Gunjan Verma, Chirag Rao +2
A fundamental problem in the design of wireless networks is to efficiently schedule transmission in a distributed manner. The main challenge stems from the fact that optimal link s…
Adversarial Examples in Constrained Domains
Ryan Sheatsley, Nicolas Papernot, Michael Weisman +2
Machine learning algorithms have been shown to be vulnerable to adversarial manipulation through systematic modification of inputs (e.g., adversarial examples) in domains such as i…
Unfolding WMMSE using Graph Neural Networks for Efficient Power Allocation
Arindam Chowdhury, Gunjan Verma, Chirag Rao +2
We study the problem of optimal power allocation in a single-hop ad hoc wireless network. In solving this problem, we depart from classical purely model-based approaches and propos…
Rapid Top-Down Synthesis of Large-Scale IoT Networks
Pradipta Ghosh, Jonathan Bunton, Dimitrios Pylorof +6
Advances in optimization and constraint satisfaction techniques, together with the availability of elastic computing resources, have spurred interest in large-scale network verific…