109 citations · 328 across the 10 of their papers we have counts for
4 papers · 1 filter
The role of data-induced randomness in quantum machine learning classification tasks
Berta Casas, Xavier Bonet-Monroig, Adrián Pérez-Salinas
Quantum machine learning (QML) has surged as a prominent area of research with the objective to go beyond the capabilities of classical machine learning models. A critical aspect o…
An Adaptive Re-evaluation Method for Evolution Strategy under Additive Noise
Catalin-Viorel Dinu, Yash J. Patel, Xavier Bonet-Monroig +1
The Covariance Matrix Adaptation Evolutionary Strategy (CMA-ES) is one of the most advanced algorithms in numerical black-box optimization. For noisy objective functions, several a…
Hierarchically discriminating Haar-randomness in quantum states from a black-box device
Xavier Bonet-Monroig, Hao Wang, Adrián Pérez-Salinas
The concept of randomness in quantum computing has been central to constructing benchmarking tools, cryptographic protocols, as well as a proof of beyond-classical computation. Dis…
Curriculum reinforcement learning for quantum architecture search under hardware errors
Yash J. Patel, Akash Kundu, Mateusz Ostaszewski +3
The key challenge in the noisy intermediate-scale quantum era is finding useful circuits compatible with current device limitations. Variational quantum algorithms (VQAs) offer a p…