Tracking the Optimal Sequence of Predictive Strategies
- 作者: V’yugin V.1, Trunov V.1
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隶属关系:
- Kharkevich Institute for Information Transmission Problems, Russian Academy of Sciences
- 期: 卷 63, 编号 12 (2018)
- 页面: 1491-1501
- 栏目: Theory and Methods of Information Processing
- URL: https://journals.rcsi.science/1064-2269/article/view/199368
- DOI: https://doi.org/10.1134/S1064226918120240
- ID: 199368
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详细
Within the prediction (decision making) theory with online experts, an adaptive algorithm is proposed that aggregates the decisions of expert strategies and incurs losses that do not exceed (up to a certain value, called a regret) the losses of the best combination of experts distributed over the prediction interval. The algorithm develops the Mixing Past Posteriors method and the AdaHedge algorithm of exponential weighting of expert decisions using an adaptive learning parameter. An estimate of the regret of the proposed algorithm is obtained. The approach proposed does not make assumptions about the nature of the data source and the limits of experts’ losses. The results of numerical experiments on mixing expert solutions using the proposed algorithm under conditions of high volatility of experts’ losses are given.
作者简介
V. V’yugin
Kharkevich Institute for Information Transmission Problems, Russian Academy of Sciences
编辑信件的主要联系方式.
Email: vyugin2@mail.ru
俄罗斯联邦, Moscow, 127051
V. Trunov
Kharkevich Institute for Information Transmission Problems, Russian Academy of Sciences
编辑信件的主要联系方式.
Email: trunov@iitp.ru
俄罗斯联邦, Moscow, 127051