4 papers
Relatively Smart II: Tractable or Semi-Supervised Instance-Optimal Learning
Shaddin Dughmi, Alireza F. Pour
We continue the study of relatively smart learning, introduced by Dughmi and Pour (2026), which asks a supervised learner to compete, marginal by marginal, with every distribution-…
Relatively Smart: A New Approach for Instance-Optimal Learning
Shaddin Dughmi, Alireza F. Pour
We revisit the framework of Smart PAC learning, which seeks supervised learners which compete with semi-supervised learners that are provided full knowledge of the marginal distrib…
Learning with Multiple Correct Answers -- Regret Bounds under Different Feedback Models
Alireza F. Pour, Farnam Mansouri, Shai Ben-David
We study the problem of learning with multiple correct answers, where each instance admits a set of valid labels. We primarily focus on the online setup, where in each round the le…
A Novel Data-Dependent Learning Paradigm for Large Hypothesis Classes
Alireza F. Pour, Shai Ben-David
We address the general task of learning with a set of candidate models that is too large to have a uniform convergence of empirical estimates to true losses. While the common appro…