Zobrazeno 1 - 6
of 6
pro vyhledávání: '"Enrico Zardini"'
Publikováno v:
IEEE Transactions on Quantum Engineering, Vol 5, Pp 1-12 (2024)
Support vector machines (SVMs) are widely used machine learning models, with formulations for both classification and regression tasks. In the last years, with the advent of working quantum annealers, hybrid SVM models characterized by quantum traini
Externí odkaz:
https://doaj.org/article/f3d02ddba02d4efb952aeb4dd37c95c9
Publikováno v:
PLoS ONE, Vol 18, Iss 11, p e0287869 (2023)
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:
https://doaj.org/article/feae80ef0dfa413dab0c351adaf6eaf3
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:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e161fea95858a7c0f67ac92909067837
Autor:
Andrea Bonomi, Thomas De Min, Enrico Zardini, Enrico Blanzieri, Valter Cavecchia, Davide Pastorello
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:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::af84ae607bb374742d1ec2ae82454b9b
Publikováno v:
GECCO
Designing optimal soft modular robots is difficult, due to non-trivial interactions between morphology and controller. Evolutionary algorithms (EAs), combined with physical simulators, represent a valid tool to overcome this issue. In this work, we i
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0564217ad819b764c81effc078e5e8d4
Publikováno v:
SciPost Physics Core, Vol 7, Iss 1, p 013 (2024)
An Ising machine is any hardware specifically designed for finding the ground state of the Ising model. Relevant examples are coherent Ising machines and quantum annealers. In this paper, we propose a new machine learning model that is based on the I
Externí odkaz:
https://doaj.org/article/7467b7a7a909402aaff7f4ceb84ab378