Learnability and Stability in the General Learning Setting.
Shai Shalev‐Shwartz, Ohad Shamir, Nathan Srebro, Karthik Sridharan · Conference on Learning Theory · 2009
We establish that stability is necessary and sufficient for learning, even in the General Learning Setting where uniform convergence conditions are not necessary for learning, and where learning might only be possible with a non-ERM learning rule. This goes beyond previous work on the relationship between stability and learnability, which focused on supervised classification and regression, where learnability is equivalent to uniform convergence and it is enough to consider the ERM.