Jul 4, 2016 · Here we analyze quantum sample complexity, where each example is a coherent quantum state. This model was introduced by Bshouty and Jackson, who ...
(2006, 2013) considered a number of quantum algorithms in learning contexts such as clustering via minimum spanning tree, divisive clustering, and k-medians,.
Here we analyze quantum sample complexity, where each example is a coherent quantum state. This model was introduced by Bshouty and Jackson (1999), who showed ...
This shows classical and quantum sample complexity are equal up to constant factors for every concept class C. 1998 ACM Subject Classification F.1.1 Models of ...
Classical machine learning. Grand goal: enable AI systems to improve themselves. Practical goal: learn“something” from given data.
Classical machine learning. Grand goal: enable AI systems to improve themselves. Practical goal: learn“something” from given data.
This work analyzes quantum sample complexity, where each example is a coherent quantum state, and shows classical and quantum sample complexity are equal up ...
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Oct 22, 2024 · Here we analyze quantum sample complexity, where each example is a coherent quantum state. This model was introduced by Bshouty and Jackson, who ...
May 6, 2011 · In this setting, quantum PAC learning and classical PAC learning are basically equivalent. The classical upper bound on sample complexity and ...
Aug 22, 2024 · CONCLUSION. This paper studies the learning of quantum measurement classes. It introduces a novel quantum algorithm called QSRM for learning ...