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cs.LG2026
How Many Domains Suffice for Domain Generalization? A Tight Characterization via the Domain Shattering Dimension
Cynthia Dwork, Lunjia Hu, Han Shao
We study a fundamental question of domain generalization: given a family of domains (i.e., data distributions), how many randomly sampled domains do we need to collect data from in…
cs.LG2025
Differentially Private Learning Beyond the Classical Dimensionality Regime
Cynthia Dwork, Pranay Tankala, Linjun Zhang
We initiate the study of differentially private learning in the proportional dimensionality regime, in which the number of data samples and problem dimension approach infin…
cs.LG2024
From Fairness to Infinity: Outcome-Indistinguishable (Omni)Prediction in Evolving Graphs
Cynthia Dwork, Chris Hays, Nicole Immorlica +2
Professional networks provide invaluable entree to opportunity through referrals and introductions. A rich literature shows they also serve to entrench and even exacerbate a status…