Results 101 to 110 of about 8,042,432 (193)

Enhanced QSVM with elitist non‐dominated sorting genetic optimisation algorithm for breast cancer diagnosis

IET Quantum Communication
Machine learning has emerged as a promising method for predicting breast cancer using quantum computation techniques. Quantum machine learning algorithms, such as quantum support vector machines (QSVMs), are demonstrating superior efficiency and economy ...
Jose P, Shanmugasundaram Hariharan, Vimaladevi Madhivanan, Sujaudeen N, Murugaperumal Krisnamoorthy, Aswani Kumar Cherukuri   +5 more
doaj   +1 more source

Basics of machine learning

In this chapter, we describe basic machine learning concepts connected to optimization and generalization. Moreover, we present a probabilistic view on machine learning that enables us to deal with uncertainty in the predictions we make.
Carleo, Giuseppe, Stornati, Paolo, Tomza, Michał, Carrasquilla, Juan, Krems, Roman, Arnold, Julian, Płodzień, Marcin, Dauphin, Alexandre, Okuła, Robert, Koch, Rouven, van Nieuwenburg, Evert, Büttner, Miriam, Gabrié, Marylou, Dunjko, Vedran, Requena, Borja, Taylor, Austin, Muñoz-Gil, Gorka, Gresch, Alexander, Vicentini, Filippo, Marquardt, Florian, Lewenstein, Maciej, Greplová, Eliška, Donatella, Kaelan, Cervera-Lierta, Alba, Wang, Lei, Nicoli, Kim A., Wetzel, Sebastian J., Vargas-Hernández, Rodrigo A.   +27 more
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Reinforcement learning-based architecture search for quantum machine learning

Quantum machine learning (QML) models use encoding circuits to map data into a quantum Hilbert space. While it is well known that the architecture of these circuits significantly influences core properties of the resulting model, they are often chosen ...
Rapp, Frederic, Huber, Marco, Roth, Marco, Kreplin, David   +3 more
core   +1 more source

Research-based interactive simulations to support quantum mechanics learning and teaching [PDF]

, 2015
Quantum mechanics holds a fascination for many students, but its mathematical complexity can present a major barrier. Traditional approaches to introductory quantum mechanics have been found to decrease student interest.
Kohnle, Antje
core   +1 more source

AutoQML - a Framework for Automated Quantum Machine Learning

In this work, we present AutoQML, a framework that seamlessly integrates Quantum Machine Learning (QML) algorithms into Automated Machine Learning (AutoML).
Tutschku, Christian Klaus, Roth, Marco, Klau, Dennis, Krause, H., Kreplin, David, Zöller, Marc-André   +5 more
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Quantum engineering of qudits with interpretable machine learning

Higher-dimensional quantum systems (qudits) offer advantages in information encoding, error resilience, and compact gate implementations, and naturally arise in platforms such as superconducting and solid-state systems. However, realistic conditions such
Paz-Silva, GA, Youssry, A, Sareen, R, Peruzzo, A, Mayevsky, Y   +4 more
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Quantum computing and quantum neural networks: their foundation, optimisation, and application [PDF]

Quantum computing is a fascinating discipline, combining the laws of quantum physics with the practicalities of computing. Certain problems could potentially be solved faster on quantum computers, and researchers hope to use them to solve difficult ...
Pointing, Jessica
core   +1 more source

Quantum machine learning with canonical variables [PDF]

Quantum Machine Intelligence
Utilising dynamic electromagnetic field control over charged particles serves as the basis for a quantum machine learning platform that operates on observables rather than directly on states. Such a platform can be physically realised in ion traps or particle confinement devices that utilise electromagnetic fields as the source of control.
openaire   +2 more sources

Assessing projected quantum kernels for the classification of IoT data

Array
The use of quantum computing for machine learning is among the most promising applications of quantum technologies. Quantum models inspired by classical algorithms are developed to explore some possible advantages over classical approaches.
Francesco D’Amore, Luca Mariani, Carlo Mastroianni, Francesco Plastina, Luca Salatino, Jacopo Settino, Andrea Vinci   +6 more
doaj   +1 more source

Quantum Techniques in Machine Learning

, 2018
In the last few years, we have witnessed an increasing interest in bridging two impor- tant research areas that fundamentally changed our way and abilities of processing information, namely Machine Learning and Quantum Computation. In the Summer 2017,
Mancini S., Di Pierro A.
core   +1 more source