论文标题
在不断变化的环境中，通过专家建议修改tin贴，以预测
Modifying Squint for Prediction with Expert Advice in a Changing Environment
论文作者
论文摘要
我们为在不断变化的环境中提供了一种在线学习的新方法，特别是通过专家建议进行预测。在非变化环境中，斜视算法的设计至少与其他已知算法相同，在特定情况下，其功能更好。但是，当使用常规的黑盒算法使适合不断变化的环境的斜视时，它会失去其有益的特性。因此，我们提供了一种新的算法，即quint-ce，适用于不断变化的环境并保留斜视的特性。
We provide a new method for online learning, specifically prediction with expert advice, in a changing environment. In a non-changing environment the Squint algorithm has been designed to always function at least as well as other known algorithms and in specific cases it functions much better. However, when using a conventional black-box algorithm to make Squint suitable for a changing environment, it loses its beneficial properties. Hence, we provide a new algorithm, Squint-CE, which is suitable for a changing environment and preserves the properties of Squint.
