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Found 5 papers, 2 papers with code
Should Bank Stress Tests Be Fair?
Regulatory stress tests have become one of the main tools for setting capital requirements at the largest U. S. banks.
Evaluating model performance under worst-case subpopulations
The performance of ML models degrades when the training population is different from that seen under operation.
Robust fine-tuning of zero-shot models
Compared to standard fine-tuning, WiSE-FT provides large accuracy improvements under distribution shift, while preserving high accuracy on the target distribution.
Ranked #12 on
Image Classification
on ObjectNet
(using extra training data)
Linear Classifiers Under Infinite Imbalance
We study the behavior of linear discriminant functions for binary classification in the infinite-imbalance limit, where the sample size of one class grows without bound while the sample size of the other remains fixed.
Peak Alignment of Gas Chromatography-Mass Spectrometry Data with Deep Learning
We show the model has very good performance (AUC $\sim 1$ for simple data sets and AUC $\sim 0. 85$ for very complex data sets).
