270 citations · 335 across the 14 of their papers we have counts for
19 papers
Rank-Adaptive Matrix-Free Atomic Quantum State Tomography
Amirhossein Taherpour, Alireza Sadeghi, Georgios B. Giannakis
Quantum state tomography estimates an unknown density operator from measurement data. Dense reconstruction however, can be impractical for many-qubit systems because the Hilbert-sp…
Distributed Learning of Quantum State Tomography Robust to Readout Errors
Amirhossein Taherpour, Alireza Sadeghi, Georgios B. Giannakis
Scalable estimation of quantum states with readout errors is a central challenge in large multiqubit systems. Existing overlapping-tomography methods improve scalability by working…
Robust, Deep, and Reinforcement Learning for Management of Communication and Power Networks
Alireza Sadeghi
This thesis develops data-driven machine learning algorithms to managing and optimizing the next-generation highly complex cyberphysical systems, which desperately need ground-brea…
Distributionally Robust Semi-Supervised Learning Over Graphs
Alireza Sadeghi, Meng Ma, Bingcong Li +1
Semi-supervised learning (SSL) over graph-structured data emerges in many network science applications. To efficiently manage learning over graphs, variants of graph neural network…
Heavy Ball Momentum for Conditional Gradient
Bingcong Li, Alireza Sadeghi, Georgios B. Giannakis
Conditional gradient, aka Frank Wolfe (FW) algorithms, have well-documented merits in machine learning and signal processing applications. Unlike projection-based methods, momentum…
Learning while Respecting Privacy and Robustness to Distributional Uncertainties and Adversarial Data
Alireza Sadeghi, Gang Wang, Meng Ma +1
Data used to train machine learning models can be adversarial--maliciously constructed by adversaries to fool the model. Challenge also arises by privacy, confidentiality, or due t…