4 citations · 4 across the 4 of their papers we have counts for
4 papers
Group-realizable multi-group learning by minimizing empirical risk
Navid Ardeshir, Samuel Deng, Daniel Hsu +1
The sample complexity of multi-group learning is shown to improve in the group-realizable setting over the agnostic setting, even when the family of groups is infinite so long as i…
Group conditional validity via multi-group learning
Samuel Deng, Navid Ardeshir, Daniel Hsu
We consider the problem of distribution-free conformal prediction and the criterion of group conditional validity. This criterion is motivated by many practical scenarios including…
Intrinsic dimensionality and generalization properties of the -norm inductive bias
Navid Ardeshir, Daniel Hsu, Clayton Sanford
We study the structural and statistical properties of -norm minimizing interpolants of datasets labeled by specific target functions. The -norm is the bas…
Support vector machines and linear regression coincide with very high-dimensional features
Navid Ardeshir, Clayton Sanford, Daniel Hsu
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 bee…