Quantum AdaBoost algorithm via cluster state

作     者：Li, Yuan 

作者机构：Shanghai Dianji Univ Dept Commun Engn Shanghai 200240 Peoples R China 

出 版 物：《INTERNATIONAL JOURNAL OF MODERN PHYSICS B》 (国际现代物理学杂志，B：凝聚态物理、统计物理、应用物理)

年 卷 期：2017年第31卷第6期

页      面：1750040-1750040页

核心收录：

学科分类：07[理学] 0702[理学-物理学] 

基　　金：Natural Science Foundation of China 

主　　题：Quantum compute AdaBoost algorithm cluster state 

摘      要：The principle and theory of quantum computation are investigated by researchers for many years, and further applied to improve the efficiency of classical machine learning algorithms. Based on physical mechanism, a quantum version of AdaBoost (Adaptive Boosting) training algorithm is proposed in this paper, of which purpose is to construct a strong classifier. In the proposed scheme with cluster state in quantum mechanism is to realize the weak learning algorithm, and then update the corresponding weight of examples. As a result, a final classifier can be obtained by combining efficiently weak hypothesis based on measuring cluster state to reweight the distribution of examples.