1 citations · 1 across the 2 of their papers we have counts for
2 papers
cs.LG2023★ 1 cited
Fantastic Generalization Measures are Nowhere to be Found
Michael Gastpar, Ido Nachum, Jonathan Shafer +1
We study the notion of a generalization bound being uniformly tight, meaning that the difference between the bound and the population loss is small for all learning algorithms and…
cs.LG2022
Finite Littlestone Dimension Implies Finite Information Complexity
Aditya Pradeep, Ido Nachum, Michael Gastpar
We prove that every online learnable class of functions of Littlestone dimension admits a learning algorithm with finite information complexity. Towards this end, we use the no…