Quantum Machine Learning bridges the gap between abstract developments in quantum computing and the applied research on machine learning. Article He is the author of Quantum Machine Learning: What Quantum Computing Means to Data Mining, available on the Elsevier Store at a 25% discount. Phys. For CDL’s quantum stream, Wittek designed boot camps, mentored founders, and attracted talent from around the world. Quantum machine learning (QML) is not one settled and homogeneous field; partly, this is because machine learning itself is quite diverse. Quantum machine learning is the integration of quantum algorithms within machine learning programs. 124, 273–296 (2000), Granade, C. E., Ferrie, C., Wiebe, N. & Cory, D. G. Robust online Hamiltonian learning. Nat. Inf. PubMed Google Scholar. & Chuang, I. L. Quantum inference on Bayesian networks. 18, 023042 (2016), Ventura, D. & Martinez, T. Quantum associative memory. 17, 41–64 (2017), Kieferova, M. & Wiebe, N. Tomography and generative data modeling via quantum Boltzmann training. 114, 200502 (2015), Zeidler, D., Frey, S., Kompa, K.-L. & Motzkus, M. Evolutionary algorithms and their application to optimal control studies. A quantum–quantum metropolis algorithm. Rev. Nature 549, 195–202 (2017). & Neven, H. Robust classification with adiabatic quantum optimization. Lett. 375, pp. , and he also holds an MSc in Mathematics. and S.L. He is interested in interdisciplinary synergies, such as scalable learning algorithms on supercomputers, computational methods in quantum simulations, and quantum machine learning.

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