1 citations · 1 across the 5 of their papers we have counts for
Showing stat.MLShow all
2 papers · 1 filter
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…