Learning DNFs under product distributions via μ-biased quantum Fourier sampling
We show that DNF formulae can be quantum PAC-learned in polynomial time under product distributions using a quantum example oracle. The current best classical algorithm runs in superpolynomial time. Our result extends the work by Bshouty and Jackson (1998) that proved that DNF formulae are efficient...
| Главные авторы: | , , |
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| Формат: | Journal article |
| Язык: | English |
| Опубликовано: |
Rinton Press
2019
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