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Found 3 papers, 2 papers with code
Group conditional validity via multi-group learning
We consider the problem of distribution-free conformal prediction and the criterion of group conditional validity.
Intrinsic dimensionality and generalization properties of the $\mathcal{R}$-norm inductive bias
We study the structural and statistical properties of $\mathcal{R}$-norm minimizing interpolants of datasets labeled by specific target functions.
Support vector machines and linear regression coincide with very high-dimensional features
The support vector machine (SVM) and minimum Euclidean norm least squares regression are two fundamentally different approaches to fitting linear models, but they have recently been connected in models for very high-dimensional data through a phenomenon of support vector proliferation, where every training example used to fit an SVM becomes a support vector.
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