Quantum learning of concentrated Boolean functions

DOI10.1007/s11128-022-03607-5OpenAlexW4288737554MaRDI QIDQ2101535

Duc Hung Pham, M. V. Panduranga Rao, Krishna V. Palem

Publication date: 6 December 2022

Published in: Quantum Information Processing (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s11128-022-03607-5

zbMATH Keywords

quantum computingPAC learningmachine learningconcentrated functions

Mathematics Subject Classification ID

Computational learning theory (68Q32) Artificial neural networks and deep learning (68T07) Quantum computation (81P68) Boolean functions (06E30)

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Quantum lower bounds for the Goldreich-Levin problem
• Oracles and queries that are sufficient for exact learning
• An improved lower bound on query complexity for quantum PAC learning
• Quantum speed-up for unsupervised learning
• Queries and concept learning
• Quantum algorithms for learning and testing juntas
• Improved bounds on quantum learning algorithms
• Quantum Computation and Quantum Information
• Learnability and the Vapnik-Chervonenkis dimension
• A theory of the learnable
• Learning DNF over the Uniform Distribution Using a Quantum Example Oracle
• Learning Decision Trees Using the Fourier Spectrum
• Polynomial-Time Algorithms for Prime Factorization and Discrete Logarithms on a Quantum Computer
• Analysis of Boolean Functions
• A quantum-inspired classical algorithm for recommendation systems
• (Nearly) Sample-Optimal Sparse Fourier Transform
• Nearly optimal sparse fourier transform
• Understanding Machine Learning

This page was built for publication: Quantum learning of concentrated Boolean functions