1 citations · 1 across the 6 of their papers we have counts for
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Universal rates of ERM for agnostic learning
Steve Hanneke, Mingyue Xu
The universal learning framework has been developed to obtain guarantees on the learning rates that hold for any fixed distribution, which can be much faster than the ones uniforml…
Universal Rates of Empirical Risk Minimization
Steve Hanneke, Mingyue Xu
The well-known empirical risk minimization (ERM) principle is the basis of many widely used machine learning algorithms, and plays an essential role in the classical PAC theory. A…
A Theory of Optimistically Universal Online Learnability for General Concept Classes
Steve Hanneke, Hongao Wang
We provide a full characterization of the concept classes that are optimistically universally online learnable with labels. The notion of optimistically universal online…
Universal Online Learning with Unbounded Losses: Memory Is All You Need
Moise Blanchard, Romain Cosson, Steve Hanneke
We resolve an open problem of Hanneke on the subject of universally consistent online learning with non-i.i.d. processes and unbounded losses. The notion of an optimistically unive…