Metarounding is an approach to convert an approximation algorithm for linear optimization over some combinatorial classes to an online linear optimization algorithm for the same class. We propose a new metarounding algorithm under a natural assumption that a relax-based approximation algorithm exists for the combinatorial class. Our algorithm is much more efficient in both theoretical and practical aspects.

翻译：元舍入是一种将针对特定组合类上的线性优化问题的近似算法转换为同类问题的在线线性优化算法的方法。我们在一个自然假设——即存在基于松弛的近似算法来处理该组合类——下提出了一种新的元舍入算法。该算法在理论与实践层面均展现出更高的效率。