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Quantum SDP Solvers: Large Speed-Ups, Optimality, and Applications to Quantum Learning.

, , , , , and . ICALP, volume 132 of LIPIcs, page 27:1-27:14. Schloss Dagstuhl - Leibniz-Zentrum für Informatik, (2019)

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Estimating expectation values using approximate quantum states., , , and . CoRR, (2020)Quantum SDP Solvers: Large Speed-Ups, Optimality, and Applications to Quantum Learning., , , , , and . ICALP, volume 132 of LIPIcs, page 27:1-27:14. Schloss Dagstuhl - Leibniz-Zentrum für Informatik, (2019)Implicit regularization and solution uniqueness in over-parameterized matrix sensing., and . CoRR, (2018)Equilibration to the non-Abelian thermal state in quantum many-body physics, , and . (2019)cite arxiv:1906.09227Comment: 5.5 pages.Estimating expectation values using approximate quantum states., , , and . Quantum, (2021)Low-rank regularization and solution uniqueness in over-parameterized matrix sensing., , and . AISTATS, volume 108 of Proceedings of Machine Learning Research, page 930-940. PMLR, (2020)Exponential Quantum Speed-ups for Semidefinite Programming with Applications to Quantum Learning., , , , , and . CoRR, (2017)Quantum Algorithm for Simulating Hamiltonian Dynamics with an Off-diagonal Series Expansion., and . Quantum, (2021)Soft-Dropout: A Practical Approach for Mitigating Overfitting in Quantum Convolutional Neural Networks., , and . CoRR, (2023)Informationally complete measurements from compressed sensing methodology., , and . CoRR, (2015)