13 citations · 33 across the 24 of their papers we have counts for
Showing 2023 · stat.MLShow all
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stat.ML2023★ 4 cited
New Equivalences Between Interpolation and SVMs: Kernels and Structured Features
Chiraag Kaushik, Andrew D. McRae, Mark A. Davenport +1
The support vector machine (SVM) is a supervised learning algorithm that finds a maximum-margin linear classifier, often after mapping the data to a high-dimensional feature space…
stat.ML2023★ 1 cited
General Loss Functions Lead to (Approximate) Interpolation in High Dimensions
Kuo-Wei Lai, Vidya Muthukumar
We provide a unified framework that applies to a general family of convex losses across binary and multiclass settings in the overparameterized regime to approximately characterize…