Agnostic learning, PAC learning, Quantum computing, VC dimension
dx.doi.org/10.4230/LIPIcs.CCC.2017.25
Progress in quantum computing:Algorithms, communication, and applications
IEEE Conference on Computational Complexity
This work was funded by the European Commission 7th Framework Programme; grant id erc/615307 - Progress in quantum computing: Algorithms, communication, and applications (QPROGRESS)
Algorithms and Complexity

Arunachalam, S, & de Wolf, R.M. (2017). Optimal quantum sample complexity of learning algorithms. In Leibniz International Proceedings in Informatics, LIPIcs: Proceedings of Conference of Computational Complexity. doi:10.4230/LIPIcs.CCC.2017.25