02014nas 2200565- 450 99632111140331620230330001146.02291-2797(CKB)2670000000550207(CONSER)cn2015300112(DE-599)ZDB2762184-4(MiFhGG)9HES(MiAaPQ)2032234(EXLCZ)99267000000055020720130404a20149999 --- aengtxtrdacontentcrdamediacrrdacarrierCanadian journal of gastroenterology & hepatology =Journal canadien de gastroenterologie et hepatologieOakville, Ontario, Canada :Pulsus Group Inc.,[2014]-1 online resourceRefereed/Peer-reviewedPrint version: Canadian journal of gastroenterology & hepatology = (DLC)cn2015300112 (OCoLC)1083569079 2291-2789 Canadian journal of gastroenterology and hepatologyJournal canadien de gastroenterologie et hepatologieCan j gastroenterol hepatolCAN J GASTROENTEROL HEPATOLGastroenterologyPeriodicalsLiverDiseasesPeriodicalsGastroentérologiePériodiquesFoieMaladiesPériodiquesGastroenterologyfast(OCoLC)fst00938842LiverDiseasesfast(OCoLC)fst01000640Periodicals.fastGastroenterologyLiverDiseasesGastroentérologieFoieMaladiesGastroenterology.LiverDiseases.616.3/3005cci1icclaccCanadian Association of Gastroenterology,Canadian Association for the Study of the Liver,JOURNAL996321111403316exl_impl conversionCanadian journal of gastroenterology & hepatology2345296UNISA04395nam 22006975 450 991030053380332120251113194454.03-319-96424-010.1007/978-3-319-96424-9(CKB)4100000006098318(MiAaPQ)EBC5504971(DE-He213)978-3-319-96424-9(PPN)229917828(MiAaPQ)EBC29095525(EXLCZ)99410000000609831820180830d2018 u| 0engurcnu||||||||txtrdacontentcrdamediacrrdacarrierSupervised Learning with Quantum Computers /by Maria Schuld, Francesco Petruccione1st ed. 2018.Cham :Springer International Publishing :Imprint: Springer,2018.1 online resource (293 pages)Quantum Science and Technology,2364-90623-319-96423-2 Introduction -- Background -- How quantum computers can classify data -- Organisation of the book -- Machine Learning -- Prediction -- Models -- Training -- Methods in machine learning -- Quantum Information -- Introduction to quantum theory -- Introduction to quantum computing -- An example: The Deutsch-Josza algorithm -- Strategies of information encoding -- Important quantum routines -- Quantum advantages -- Computational complexity of learning -- Sample complexity -- Model complexity -- Information encoding -- Basis encoding -- Amplitude encoding -- Qsample encoding -- Hamiltonian encoding -- Quantum computing for inference -- Linear models -- Kernel methods -- Probabilistic models -- Quantum computing for training -- Quantum blas -- Search and amplitude amplification -- Hybrid training for variational algorithms -- Quantum adiabatic machine learning -- Learning with quantum models -- Quantum extensions of Ising-type models -- Variational classifiers and neural networks -- Other approaches to buildquantum models -- Prospects for near-term quantum machine learning -- Small versus big data -- Hybrid versus fully coherent approaches -- Qualitative versus quantitative advantages -- What machine learning can do for quantum computing -- References.Quantum machine learning investigates how quantum computers can be used for data-driven prediction and decision making. The books summarises and conceptualises ideas of this relatively young discipline for an audience of computer scientists and physicists from a graduate level upwards. It aims at providing a starting point for those new to the field, showcasing a toy example of a quantum machine learning algorithm and providing a detailed introduction of the two parent disciplines. For more advanced readers, the book discusses topics such as data encoding into quantum states, quantum algorithms and routines for inference and optimisation, as well as the construction and analysis of genuine ``quantum learning models''. A special focus lies on supervised learning, and applications for near-term quantum devices.Quantum Science and Technology,2364-9062Quantum physicsQuantum computersPattern recognition systemsSpintronicsMathematical physicsArtificial intelligenceQuantum PhysicsQuantum ComputingAutomated Pattern RecognitionSpintronicsTheoretical, Mathematical and Computational PhysicsArtificial IntelligenceQuantum physics.Quantum computers.Pattern recognition systems.Spintronics.Mathematical physics.Artificial intelligence.Quantum Physics.Quantum Computing.Automated Pattern Recognition.Spintronics.Theoretical, Mathematical and Computational Physics.Artificial Intelligence.530.1201514Schuld Mariaauthttp://id.loc.gov/vocabulary/relators/aut878448Petruccione F(Francesco),authttp://id.loc.gov/vocabulary/relators/autBOOK9910300533803321Supervised Learning with Quantum Computers2533821UNINA