The geometry of quantum learning
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SCOPUS
- Title
- The geometry of quantum learning
- Authors
- Hunziker, M; Meyer, DA; Park, J; Pommersheim, J; Rothstein, M
- Date Issued
- 2010-06
- Publisher
- Springer
- Abstract
- Concept learning provides a natural framework in which to place the problems solved by the quantum algorithms of Bernstein-Vazirani and Grover. By combining the tools used in these algorithms-quantum fast transforms and amplitude amplification-with a novel (in this context) tool-a solution method for geometrical optimization problems-we derive a general technique for quantum concept learning. We name this technique "Amplified Impatient Learning" and apply it to construct quantum algorithms solving two new problems: Battleship and Majority, more efficiently than is possible classically.
- Keywords
- Quantum algorithms; Procrustes problem; ALGORITHMS; BOUNDS
- URI
- https://oasis.postech.ac.kr/handle/2014.oak/25907
- DOI
- 10.1007/S11128-009-0129-6
- ISSN
- 1570-0755
- Article Type
- Article
- Citation
- QUANTUM INFORMATION PROCESSING, vol. 9, no. 3, page. 321 - 341, 2010-06
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