Quantum machine learning: a classical perspective. - Carlo Ciliberto; Mark Herbster; Alessandro Davide Ialongo; Massimiliano Pontil; Andrea Rocchetto; Simone Severini; Leonard Wossnig (CoRR, 2017)

Experimental learning of quantum states. - Andrea Rocchetto; Scott Aaronson; Simone Severini; Gonzalo Carvacho; Davide Poderini; Iris Agresti; Marco Bentivegna; Fabio Sciarrino (CoRR, 2017)

Learning DNFs under product distributions via μ-biased quantum Fourier sampling. - Varun Kanade; Andrea Rocchetto; Simone Severini (CoRR, 2018)

Stabiliser states are efficiently PAC-learnable. - Andrea Rocchetto (Quantum Inf. Comput., 2018)

mu - biased quantum Fourier sampling. - Varun Kanade; Andrea Rocchetto; Simone Severini (Quantum Inf. Comput., 2019)

Algorithmic models in quantum mechanics. - Andrea Rocchetto (2019)

Fast quantum learning with statistical guarantees. - Carlo Ciliberto; Andrea Rocchetto; Alessandro Rudi; Leonard Wossnig (CoRR, 2020)

Approximating Hamiltonian dynamics with the Nyström method. - Alessandro Rudi; Leonard Wossnig; Carlo Ciliberto; Andrea Rocchetto; Massimiliano Pontil; Simone Severini (Quantum, 2020)