量子最佳臂辨识

Q4 Computer Science

Performance Evaluation Review Pub Date : 2023-09-28 DOI:10.1145/3626570.3626596

Xuchuang Wang, Yu-Zhen Janice Chen, Matheus Guedes de Andrade, Mohammad Hajiesmaili, John C.S. Lui, Don Towsley

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引用次数: 0

摘要

构建量子计算机的最新进展[1]设想了量子算法在不久的将来的广泛应用。利用量子计算机的优势，人们不仅可以加快基本算法，如非结构化搜索[6]和因子分解[11]，还可以加快最近的机器学习算法[3]。在本文中，我们研究了一个典型的任务-多武装匪徒的最佳武器识别的量子加速。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Quantum Best Arm Identification

Recent progress on building quantum computers [1] envisages wide applications of quantum algorithms in the near future. With the advantage of quantum computer, one can speed up not only fundamental algorithms, e.g., unstructured search [6] and factoring [11], but recent machine learning algorithms [3] as well. In this paper, we study the quantum speedup on a canonical task of reinforcement learning-best arm identification in multi-armed bandits.

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来源期刊

Performance Evaluation Review Computer Science-Computer Networks and Communications

CiteScore

1.00

自引率

0.00%

发文量

193