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01/27/2023
Robust variance-regularized risk minimization with concomitant scaling
Under losses which are potentially heavy-tailed, we consider the task of...
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03/28/2022
Risk regularization through bidirectional dispersion
Many alternative notions of "risk" (e.g., CVaR, entropic risk, DRO risk)...
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10/11/2021
Designing off-sample performance metrics
Modern machine learning systems are traditionally designed and tested wi...
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05/24/2021
Robust learning with anytime-guaranteed feedback
Under data distributions which may be heavy-tailed, many stochastic grad...
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05/11/2021
Spectral risk-based learning using unbounded losses
In this work, we consider the setting of learning problems under a wide ...
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12/14/2020
Better scalability under potentially heavy-tailed feedback
We study scalable alternatives to robust gradient descent (RGD) techniqu...
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12/04/2020
Non-monotone risk functions for learning
In this paper we consider generalized classes of potentially non-monoton...
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07/09/2020
Making learning more transparent using conformalized performance prediction
In this work, we study some novel applications of conformal inference te...
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06/03/2020
Learning with CVaR-based feedback under potentially heavy tails
We study learning algorithms that seek to minimize the conditional value...
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06/02/2020
Improved scalability under heavy tails, without strong convexity
Real-world data is laden with outlying values. The challenge for machine...
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06/01/2020
Better scalability under potentially heavy-tailed gradients
We study a scalable alternative to robust gradient descent (RGD) techniq...
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06/25/2019
Distribution-robust mean estimation via smoothed random perturbations
We consider the problem of mean estimation assuming only finite variance...
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05/20/2019
PAC-Bayes under potentially heavy tails
We derive PAC-Bayesian learning guarantees for heavy-tailed losses, and ...
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10/15/2018
Robust descent using smoothed multiplicative noise
To improve the off-sample generalization of classical procedures minimiz...
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10/11/2018
Classification using margin pursuit
In this work, we study a new approach to optimizing the margin distribut...
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06/01/2017