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An improved lower bound on query complexity for quantum PAC learning
Authors:Chi Zhang
Affiliation:Department of Computer Science, Columbia University, New York, NY 10027, USA
Abstract:In this paper, we study the quantum PAC learning model, offering an improved lower bound on the query complexity. For a concept class with VC dimension d, the lower bound is View the MathML source for ? accuracy and 1−δ confidence, where e can be an arbitrarily small positive number. The lower bound is very close to the best lower bound known on query complexity for the classical PAC learning model, which is View the MathML source.
Keywords:PAC (Probably Approximately Correct) learning  Lower bound  Quantum algorithm  VC dimension  Computational complexity
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