Zobrazeno 1 - 10
of 193
pro vyhledávání: '"Blanzieri Enrico"'
Autor:
Zardini, Enrico, Delilbasic, Amer, Blanzieri, Enrico, Cavallaro, Gabriele, Pastorello, Davide
Publikováno v:
IEEE Transactions on Quantum Engineering 5 (2024) 1-12
Support vector machines (SVMs) are widely used machine learning models (e.g., in remote sensing), with formulations for both classification and regression tasks. In the last years, with the advent of working quantum annealers, hybrid SVM models chara
Externí odkaz:
http://arxiv.org/abs/2403.08584
Publikováno v:
Quantum Information and Computation 24 3-4 (2024) 181-209
In the current era, known as Noisy Intermediate-Scale Quantum (NISQ), encoding large amounts of data in the quantum devices is challenging and the impact of noise significantly affects the quality of the obtained results. A viable approach for the ex
Externí odkaz:
http://arxiv.org/abs/2311.09750
Publikováno v:
Interaction Studies, Vol. 23, Dec 2022, p.469-512
The development of artificial agents for social interaction pushes to enrich robots with social skills and knowledge about (local) social norms. One possibility is to distinguish the expressive and the functional orders during a human-robot interacti
Externí odkaz:
http://arxiv.org/abs/2308.03146
Autor:
Pastorello, Davide, Blanzieri, Enrico
This paper focuses on the construction of a general parametric model that can be implemented executing multiple swap tests over few qubits and applying a suitable measurement protocol. The model turns out to be equivalent to a two-layer feedforward n
Externí odkaz:
http://arxiv.org/abs/2307.01017
Publikováno v:
Quantum Machine Intelligence 6 1.23 (2024) 1-22
The k-nearest neighbors (k-NN) is a basic machine learning (ML) algorithm, and several quantum versions of it, employing different distance metrics, have been presented in the last few years. Although the Euclidean distance is one of the most widely
Externí odkaz:
http://arxiv.org/abs/2305.04287
Autor:
Bonomi, Andrea, De Min, Thomas, Zardini, Enrico, Blanzieri, Enrico, Cavecchia, Valter, Pastorello, Davide
Publikováno v:
Quantum Information and Computation 22 3-4 (2022) 181-208
This paper presents the details and testing of two implementations (in C++ and Python) of the hybrid quantum-classical algorithm Quantum Annealing Learning Search (QALS) on a D-Wave quantum annealer. QALS was proposed in 2019 as a novel technique to
Externí odkaz:
http://arxiv.org/abs/2212.11132
Publikováno v:
Journal of Integrative Bioinformatics, Vol 5, Iss 1, Pp 57-71 (2008)
The paradigmatic shift occurred in biology that led first to high-throughput experimental techniques and later to computational systems biology must be applied also to the analysis paradigm of the relation between local models and data to obtain an e
Externí odkaz:
https://doaj.org/article/ea4ce73792e340b6855e478265be8bde
Autor:
Blanzieri, Enrico, Pastorello, Davide, Cavecchia, Valter, Rumyantsev, Alexander, Maltseva, Mariia
In this paper we introduce the Tabu Enhanced Hybrid Quantum Optimization metaheuristic approach useful for optimization problem solving on a quantum hardware. We address the theoretical convergence of the proposed scheme from the viewpoint of the col
Externí odkaz:
http://arxiv.org/abs/2209.01799
Publikováno v:
PLOS ONE 18 11 (2023) 1-28
In the current era, quantum resources are extremely limited, and this makes difficult the usage of quantum machine learning (QML) models. Concerning the supervised tasks, a viable approach is the introduction of a quantum locality technique, which al
Externí odkaz:
http://arxiv.org/abs/2205.05333
Autor:
Zardini, Enrico, Rizzoli, Massimo, Dissegna, Sebastiano, Blanzieri, Enrico, Pastorello, Davide
Publikováno v:
Quantum Information and Computation 22 15-16 (2022) 1320-1350
Bayesian networks are widely used probabilistic graphical models, whose structure is hard to learn starting from the generated data. O'Gorman et al. have proposed an algorithm to encode this task, i.e., the Bayesian network structure learning (BSNL),
Externí odkaz:
http://arxiv.org/abs/2204.03526