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Trading off Consistency and Dimensionality of Convex Surrogates for the Mode
We investigate ways to trade off surrogate loss dimension, the number of problem instances, and restricting the region of consistency in the simplex for multiclass classification.
The Structured Abstain Problem and the Lovász Hinge
The Lov\'asz hinge is a convex surrogate recently proposed for structured binary classification, in which $k$ binary predictions are made simultaneously and the error is judged by a submodular set function.
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