7 citations · 10 across the 21 of their papers we have counts for
Showing stat.MLShow all
3 papers · 1 filter
stat.ML2026
The optimal information complexity of VC learning
Steve Hanneke, Juexiao Wang
Steinke and Zakynthinou(2020) introduces the Conditional Mutual Information (CMI) framework of analyzing the information complexity of learning algorithms based on algorithm-depend…
stat.ML2026
PAC Learning with Bandit Feedback: Sharp Sample Complexity in the Realizable Setting
Steve Hanneke, Qinglin Meng, Shay Moran +1
We study the problem of multiclass PAC learning with bandit feedback in the realizable setting. In this framework, there is an unknown data distribution over an instance space $\ma…
stat.ML2024
On the ERM Principle in Meta-Learning
Yannay Alon, Steve Hanneke, Shay Moran +1
Classic supervised learning involves algorithms trained on labeled examples to produce a hypothesis aimed at performing well on unseen examples. Meta-learni…