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Quantum Circuit Design Gate Engineering Quantum Simulation Entanglement Theory Quantum Correlations Quantum State Preparation Representation

Improved Quantum Boosting

arXiv
Authors: Adam Izdebski, Ronald de Wolf

Year

2020

Paper ID

20621

Status

Preprint

Abstract Read

~2 min

Abstract Words

107

Citations

N/A

Abstract

Boosting is a general method to convert a weak learner (which generates hypotheses that are just slightly better than random) into a strong learner (which generates hypotheses that are much better than random). Recently, Arunachalam and Maity gave the first quantum improvement for boosting, by combining Freund and Schapire's AdaBoost algorithm with a quantum algorithm for approximate counting. Their booster is faster than classical boosting as a function of the VC-dimension of the weak learner's hypothesis class, but worse as a function of the quality of the weak learner. In this paper we give a substantially faster and simpler quantum boosting algorithm, based on Servedio's SmoothBoost algorithm.

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  • This paper contributes to the Quantum Simulation research area in the Quantum Articles archive.
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  • Boosting is a general method to convert a weak learner (which generates hypotheses that are just slightly better than random) into a strong learner (which generates hypotheses...

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References & Citation Signals

[1] DOI https://doi.org/arXiv:2009.08360 [2] arXiv https://arxiv.org/abs/2009.08360 [3] Publisher https://arxiv.org/abs/2009.08360

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