On-line Learning and the Metrical Task System Problem
作者:Avrim Blum, Carl Burch
摘要
The problem of combining expert advice, studied extensively in the Computational Learning Theory literature, and the Metrical Task System (MTS) problem, studied extensively in the area of On-line Algorithms, contain a number of interesting similarities. In this paper we explore the relationship between these problems and show how algorithms designed for each can be used to achieve good bounds and new approaches for solving the other. Specific contributions of this paper include:
论文关键词:on-line learning, metrical task systems, combining expert advice, randomized on-line algorithms
论文评审过程:
论文官网地址:https://doi.org/10.1023/A:1007621832648