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Andrea Rocchetto
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2020 – today
- 2020
- [j3]Alessandro Rudi, Leonard Wossnig, Carlo Ciliberto, Andrea Rocchetto, Massimiliano Pontil, Simone Severini:
Approximating Hamiltonian dynamics with the Nyström method. Quantum 4: 234 (2020) - [i6]Carlo Ciliberto, Andrea Rocchetto, Alessandro Rudi, Leonard Wossnig:
Fast quantum learning with statistical guarantees. CoRR abs/2001.10477 (2020)
2010 – 2019
- 2019
- [b1]Andrea Rocchetto:
Algorithmic models in quantum mechanics. University of Oxford, UK, 2019 - [j2]Varun Kanade, Andrea Rocchetto, Simone Severini:
mu - biased quantum Fourier sampling. Quantum Inf. Comput. 19(15&16): 1261-1278 (2019) - 2018
- [j1]Andrea Rocchetto:
Stabiliser states are efficiently PAC-learnable. Quantum Inf. Comput. 18(7&8): 541-552 (2018) - [i5]Varun Kanade, Andrea Rocchetto, Simone Severini:
Learning DNFs under product distributions via μ-biased quantum Fourier sampling. CoRR abs/1802.05690 (2018) - [i4]Alessandro Rudi, Leonard Wossnig, Carlo Ciliberto, Andrea Rocchetto, Massimiliano Pontil, Simone Severini:
Approximating Hamiltonian dynamics with the Nyström method. CoRR abs/1804.02484 (2018) - 2017
- [i3]Andrea Rocchetto:
Stabiliser states are efficiently PAC-learnable. CoRR abs/1705.00345 (2017) - [i2]Carlo Ciliberto, Mark Herbster, Alessandro Davide Ialongo, Massimiliano Pontil, Andrea Rocchetto, Simone Severini, Leonard Wossnig:
Quantum machine learning: a classical perspective. CoRR abs/1707.08561 (2017) - [i1]Andrea Rocchetto, Scott Aaronson, Simone Severini, Gonzalo Carvacho, Davide Poderini, Iris Agresti, Marco Bentivegna, Fabio Sciarrino:
Experimental learning of quantum states. CoRR abs/1712.00127 (2017)
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