424 citations · 855 across the 27 of their papers we have counts for
5 papers · 1 filter
An Empirical Analysis on the Effectiveness of the Variational Quantum Linear Solver
Gloria Turati, Alessia Marruzzo, Maurizio Ferrari Dacrema +1
Variational Quantum Algorithms (VQAs) have emerged as promising methods for tackling complex problems on near-term quantum devices. Among these algorithms, the Variational Quantum…
Reinforcement Learning for Variational Quantum Circuits Design
Simone Foderà, Gloria Turati, Riccardo Nembrini +2
Variational Quantum Algorithms have emerged as promising tools for solving optimization problems on quantum computers. These algorithms leverage a parametric quantum circuit called…
Adaptive Learning for Quantum Linear Regression
Costantino Carugno, Maurizio Ferrari Dacrema, Paolo Cremonesi
The recent availability of quantum annealers as cloud-based services has enabled new ways to handle machine learning problems, and several relevant algorithms have been adapted to…
Analyzing the Effectiveness of Quantum Annealing with Meta-Learning
Riccardo Pellini, Maurizio Ferrari Dacrema
The field of Quantum Computing has gathered significant popularity in recent years and a large number of papers have studied its effectiveness in tackling many tasks. We focus in p…
Automated Off-Policy Estimator Selection via Supervised Learning
Nicolò Felicioni, Michael Benigni, Maurizio Ferrari Dacrema
The Off-Policy Evaluation (OPE) problem consists of evaluating the performance of counterfactual policies with data collected by another one. To solve the OPE problem, we resort to…