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We present two new results about exact learning by quantum computers.
A theory of the learnable
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Quantum complexity theory
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Learning DNF over the uniform distribution using a quantum example oracle
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Equivalences and separations between quantum and classical learnability
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All quantum adversary methods are equivalent
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Sample-optimal Fourier sampling in any constant dimension
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An introduction to quantum machine learning
M. Schuld, I. Sinayskiy, and F. Petruccione · 2014
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Quantum Machine Learning: What Quantum Computing Means to Data Mining
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Advances in quantum machine learning, 2015
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The list-decoding size of Fourier-sparse Boolean functions
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Quantum Computation and Quantum Information: 10th Anniversary Edition
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Tight Chang’s-lemma-type bounds for Boolean functions, 2020
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H. Hassanieh, P. Indyk, D. Katabi, and E. Price · 2012
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Quantum machine learning
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Optimal quantum sample complexity of learning algorithms
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Machine learning & artificial intelligence in the quantum domain: a review of recent progress
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