论文标题
具有任意依赖性回答的普遍一致的在线学习
Universally Consistent Online Learning with Arbitrarily Dependent Responses
论文作者
论文摘要
这项工作提供了一个在线学习规则，该规则仅在x过程的条件下（x，y）对的流程中普遍一致。作为一种特殊情况，条件接纳了（x，y）上的所有过程，使得x上的过程是固定的。这概括了过去的结果，这需要（x，y）上的联合过程的平稳性，并要求此过程为ergodic。特别是，这意味着，出于普遍稳定的在线学习目的，恐怖性是多余的。
This work provides an online learning rule that is universally consistent under processes on (X,Y) pairs, under conditions only on the X process. As a special case, the conditions admit all processes on (X,Y) such that the process on X is stationary. This generalizes past results which required stationarity for the joint process on (X,Y), and additionally required this process to be ergodic. In particular, this means that ergodicity is superfluous for the purpose of universally consistent online learning.
