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04/13/2023
Bayes classifier cannot be learned from noisy responses with unknown noise rates
Training a classifier with noisy labels typically requires the learner t...
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02/20/2023
Simple Disentanglement of Style and Content in Visual Representations
Learning visual representations with interpretable features, i.e., disen...
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09/14/2022
RMExplorer: A Visual Analytics Approach to Explore the Performance and the Fairness of Disease Risk Models on Population Subgroups
Disease risk models can identify high-risk patients and help clinicians ...
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06/07/2022
How does overparametrization affect performance on minority groups?
The benefits of overparameterization for the overall performance of mode...
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05/26/2022
Understanding new tasks through the lens of training data via exponential tilting
Deploying machine learning models to new tasks is a major challenge desp...
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05/26/2022
Predictor-corrector algorithms for stochastic optimization under gradual distribution shift
Time-varying stochastic optimization problems frequently arise in machin...
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11/21/2021
A linear adjustment based approach to posterior drift in transfer learning
We present a new model and methods for the posterior drift problem where...
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03/30/2021
Statistical inference for individual fairness
As we rely on machine learning (ML) models to make more consequential de...
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11/06/2020
There is no trade-off: enforcing fairness can improve accuracy
One of the main barriers to the broader adoption of algorithmic fairness...
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03/23/2020
Minimax optimal approaches to the label shift problem
We study minimax rates of convergence in the label shift problem. In add...
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12/26/2019
