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01/28/2022
Understanding Why Generalized Reweighting Does Not Improve Over ERM
Empirical risk minimization (ERM) is known in practice to be non-robust ...
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10/26/2021
Boosted CVaR Classification
Many modern machine learning tasks require models with high tail perform...
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06/11/2021
DORO: Distributional and Outlier Robust Optimization
Many machine learning tasks involve subpopulation shift where the testin...
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12/19/2020
Fundamental Limits and Tradeoffs in Invariant Representation Learning
Many machine learning applications involve learning representations that...
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06/29/2020
Sharp Statistical Guarantees for Adversarially Robust Gaussian Classification
Adversarial robustness has become a fundamental requirement in modern ma...
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05/26/2020
Class-Weighted Classification: Trade-offs and Robust Approaches
We address imbalanced classification, the problem in which a label may h...
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03/06/2020
Learning Complexity of Simulated Annealing
Simulated annealing is an effective and general means of optimization. I...
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01/08/2020
MACER: Attack-free and Scalable Robust Training via Maximizing Certified Radius
Adversarial training is one of the most popular ways to learn robust mod...
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10/30/2019
Optimal Analysis of Subset-Selection Based L_p Low Rank Approximation
We study the low rank approximation problem of any given matrix A over R...
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09/29/2019
Learning Sparse Nonparametric DAGs
We develop a framework for learning sparse nonparametric directed acycli...
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06/03/2019
Adversarially Robust Generalization Just Requires More Unlabeled Data
Neural network robustness has recently been highlighted by the existence...
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10/19/2018
Bilu-Linial stability, certified algorithms and the Independent Set problem
We study the notion of Bilu-Linial stability in the context of Independe...
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09/10/2018
Sample Complexity of Nonparametric Semi-Supervised Learning
We study the sample complexity of semi-supervised learning (SSL) and int...
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02/12/2018
