Uniform stability of a learning algorithm
= Uniform stability of a learning algorithm
This is a uniform version of <Stability (learning theory)> for learning algorithms. A learning algorithm has uniform stability $\beta$ for a loss when replacing one training example changes the loss at every test example by at most $\beta$.