2 citations · 3 across the 15 of their papers we have counts for
8 papers · 1 filter
PAC Learning with Query Feedback
Chase Hutton, Adam Melrod, Han Shao
We study realizable multiclass PAC learning with query feedback, where each training example provides a single binary response indicating whether its true label belongs to a chosen…
How Many Repeated Pairwise Comparisons Are Needed for Ranking under Heterogeneity?
Shashaank Aiyer, Han Shao
We study ranking models by population-average utility from pairwise comparisons when preferences vary across users and tasks. Prior work shows that a single comparison per user can…
Pluralistic Leaderboards
Nika Haghtalab, Ariel D. Procaccia, Han Shao +2
Recent leaderboard-based evaluations of large language models aggregate user feedback by fitting a Bradley--Terry model to pairwise comparisons, producing a single global ranking b…
Scale-Sensitive Shattering: Learnability and Evaluability at Optimal Scale
Shashaank Aiyer, Yishay Mansour, Shay Moran +2
We study the optimal scale at which real-valued function classes exhibit uniform convergence and learnability. Our main result establishes a scale-sensitive generalization of the f…
Online Set Learning from Precision and Recall Feedback
Lee Cohen, Yishay Mansour, Shay Moran +1
We consider the problem of learning an unknown subset of a domain in an online setting. In each round , the learner predicts a set of items and receive…
A Theoretical Framework for Statistical Evaluability of Generative Models
Shashaank Aiyer, Yishay Mansour, Shay Moran +1
Statistical evaluation aims to estimate the generalization performance of a model using held-out i.i.d. test data sampled from the ground-truth distribution. In supervised learning…
Equitable Evaluation via Elicitation
Elbert Du, Cynthia Dwork, Lunjia Hu +3
Individuals with similar qualifications and skills may vary in their demeanor, or outward manner: some tend toward self-promotion while others are modest to the point of omitting c…
On Randomized Algorithms in Online Strategic Classification
Chase Hutton, Adam Melrod, Han Shao
Online strategic classification studies settings in which agents strategically modify their features to obtain favorable predictions. For example, given a classifier that determine…