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Jacob M. Taylor

Colloquium: Advances in automation of quantum dot devices control

Dec 17, 2021
Justyna P. Zwolak, Jacob M. Taylor

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* 19 pages, 9 figures

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Theoretical bounds on data requirements for the ray-based classification

Mar 17, 2021
Brian J. Weber, Sandesh S. Kalantre, Thomas McJunkin, Jacob M. Taylor, Justyna P. Zwolak

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* 16 pages, 5 figures

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Exponential improvements for quantum-accessible reinforcement learning

Aug 08, 2018
Vedran Dunjko, Yi-Kai Liu, Xingyao Wu, Jacob M. Taylor

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* 14+13 pages, 4 figures; The updated version is simplified, and more concisely presented

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Quantum-enhanced machine learning

Oct 26, 2016
Vedran Dunjko, Jacob M. Taylor, Hans J. Briegel

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* Phys. Rev. Lett. 117, 130501 (2016)
* 5+15 pages. This paper builds upon and mostly supersedes arXiv:1507.08482. In addition to results provided in this previous work, here we achieve learning improvements in more general environments, and provide connections to other work in quantum machine learning. Explicit constructions of oracularized environments given in arXiv:1507.08482 are omitted in this version

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Framework for learning agents in quantum environments

Jul 30, 2015
Vedran Dunjko, Jacob M. Taylor, Hans J. Briegel

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* 39 pages, 7 figures

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