Now showing items 1-2 of 2
Learning by Augmenting Rules and Accumulating Censors
This paper is a synthesis of several sets of ideas: ideas about learning from precedents and exercises, ideas about learning using near misses, ideas about generalizing if-then rules, and ideas about using censors to ...
Sufficient Conditions for Uniform Stability of Regularization Algorithms
In this paper, we study the stability and generalization properties of penalized empirical-risk minimization algorithms. We propose a set of properties of the penalty term that is sufficient to ensure uniform ?-stability: ...