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人工智能论文:预测的几何终止版本基于势能的新边界(New Potential-Based Bounds for the Geometric-Stopping V

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yyshrrrr 发表于 2019-12-9 14:02:48 | 显示全部楼层 |阅读模式
yyshrrrr 2019-12-9 14:02:48 145 0 显示全部楼层
人工智能论文:预测的几何终止版本基于势能的新边界(New Potential-Based Bounds for the Geometric-Stopping Version of  Prediction with Expert Advice)这项工作通过专家建议解决了在线预测的经典机器学习问题。以前使用最佳控制理论的验证论点(Kobzar,Kohn和Wang,基于新势垒的专家建议进行预测)(2019年),针对此问题的固定水平版本开发了基于势的框架。本文将这个框架扩展到了随机(几何)停止版本。利用这些思想,我们根据固定水平版本使用的电势专家建议,构建了预测的几何转换电势。这种构造导致新的明确的上下限,并与几何问题的特定对手和玩家策略相关联。我们确定了这些界限为最新状态的体制。
This work addresses the classic machine learning problem of online predictionwith expert advice.A potential-based framework for the fixed horizon versionof this problem was previously developed using verification arguments fromoptimal control theory (Kobzar, Kohn and Wang, New Potential-Based Bounds forPrediction with Expert Advice (2019)).This paper extends this framework to therandom (geometric) stopping version.Taking advantage of these ideas, we construct potentials for the geometricversion of prediction with expert advice from potentials used for the fixedhorizon version.This construction leads to new explicit lower and upper boundsassociated with specific adversary and player strategies for the geometricproblem.We identify regimes where these bounds are state of the art.人工智能论文:预测的几何终止版本基于势能的新边界(New Potential-Based Bounds for the Geometric-Stopping Version of  Prediction with Expert Advice)
URL地址:https://arxiv.org/abs/1912.03132     ----pdf下载地址:https://arxiv.org/pdf/1912.03132    ----人工智能论文:预测的几何终止版本基于势能的新边界(New Potential-Based Bounds for the Geometric-Stopping Version of  Prediction with Expert Advice)
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