98 citations · 237 across the 9 of their papers we have counts for
9 papers
Offline to Online Learning for Real-Time Bandwidth Estimation
Aashish Gottipati, Sami Khairy, Gabriel Mittag +2
Real-time video applications require accurate bandwidth estimation (BWE) to maintain user experience across varying network conditions. However, increasing network heterogeneity ch…
Numerical evidence against advantage with quantum fidelity kernels on classical data
Lucas Slattery, Ruslan Shaydulin, Shouvanik Chakrabarti +3
Quantum machine learning techniques are commonly considered one of the most promising candidates for demonstrating practical quantum advantage. In particular, quantum kernel method…
Multifidelity Reinforcement Learning with Control Variates
Sami Khairy, Prasanna Balaprakash
In many computational science and engineering applications, the output of a system of interest corresponding to a given input can be queried at different levels of fidelity with di…
Data-Driven Random Access Optimization in Multi-Cell IoT Networks with NOMA
Sami Khairy, Prasanna Balaprakash, Lin X. Cai +1
Non-orthogonal multiple access (NOMA) is a key technology to enable massive machine type communications (mMTC) in 5G networks and beyond. In this paper, NOMA is applied to improve…
A Gradient-Aware Search Algorithm for Constrained Markov Decision Processes
Sami Khairy, Prasanna Balaprakash, Lin X. Cai
The canonical solution methodology for finite constrained Markov decision processes (CMDPs), where the objective is to maximize the expected infinite-horizon discounted rewards sub…
Optimizing Non-Orthogonal Multiple Access in Random Access Networks
Ziru Chen, Yong Liu, Sami Khairy +3
Non-orthogonal multiple access (NOMA) has been considered as a promising solution for improving the spectrum efficiency of next-generation wireless networks. In this paper, the per…
Constrained Deep Reinforcement Learning for Energy Sustainable Multi-UAV based Random Access IoT Networks with NOMA
Sami Khairy, Prasanna Balaprakash, Lin X. Cai +1
In this paper, we apply the Non-Orthogonal Multiple Access (NOMA) technique to improve the massive channel access of a wireless IoT network where solar-powered Unmanned Aerial Vehi…
Learning to Optimize Variational Quantum Circuits to Solve Combinatorial Problems
Sami Khairy, Ruslan Shaydulin, Lukasz Cincio +2
Quantum computing is a computational paradigm with the potential to outperform classical methods for a variety of problems. Proposed recently, the Quantum Approximate Optimization…
Reinforcement-Learning-Based Variational Quantum Circuits Optimization for Combinatorial Problems
Sami Khairy, Ruslan Shaydulin, Lukasz Cincio +2
Quantum computing exploits basic quantum phenomena such as state superposition and entanglement to perform computations. The Quantum Approximate Optimization Algorithm (QAOA) is ar…