TL;DR本文证明了多分类问题的效率最优解必须是不正确的,并提出了一种基于generalized linear classifiers 的效率最优解的算法。
Abstract
The fundamental theorem of statistical learning states that for binary classification problems, any Empirical Risk Minimization (ERM) learning rule has close to optimal sample complexity. In this paper we seek fo