617 citations · 746 across the 17 of their papers we have counts for
5 papers · 1 filter
Outliers with Opposing Signals Have an Outsized Effect on Neural Network Optimization
Elan Rosenfeld, Andrej Risteski
We identify a new phenomenon in neural network optimization which arises from the interaction of depth and a particular heavy-tailed structure in natural data. Our result offers in…
One-Shot Strategic Classification Under Unknown Costs
Elan Rosenfeld, Nir Rosenfeld
The goal of strategic classification is to learn decision rules which are robust to strategic input manipulation. Earlier works assume that these responses are known; while some re…
Identifying Representations for Intervention Extrapolation
Sorawit Saengkyongam, Elan Rosenfeld, Pradeep Ravikumar +2
The premise of identifiable and causal representation learning is to improve the current representation learning paradigm in terms of generalizability or robustness. Despite recent…
Learning Linear Causal Representations from Interventions under General Nonlinear Mixing
Simon Buchholz, Goutham Rajendran, Elan Rosenfeld +3
We study the problem of learning causal representations from unknown, latent interventions in a general setting, where the latent distribution is Gaussian but the mixing function i…
(Almost) Provable Error Bounds Under Distribution Shift via Disagreement Discrepancy
Elan Rosenfeld, Saurabh Garg
We derive an (almost) guaranteed upper bound on the error of deep neural networks under distribution shift using unlabeled test data. Prior methods either give bounds that are vacu…