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cs.LG2024
Robust support vector machines via conic optimization
Valentina Cepeda, Andrés Gómez, Shaoning Han
We consider the problem of learning support vector machines robust to uncertainty. It has been established in the literature that typical loss functions, including the hinge loss,…
cs.LG2023★ 1 cited
Learning Optimal Classification Trees Robust to Distribution Shifts
Nathan Justin, Sina Aghaei, Andrés Gómez +1
We consider the problem of learning classification trees that are robust to distribution shifts between training and testing/deployment data. This problem arises frequently in high…