convex surrogate

An Embedding Framework for the Design and Analysis of Consistent Polyhedral Surrogates JMLR 2024 The Structured Abstain Problem and the Lovász Hinge COLT 2022 Agnostic Learning of Halfspaces with Gradient Descent via Soft Margins ICML 2021 Risk Bounds and Calibration for a Smart Predict-then-Optimize Method NeurIPS 2021 Unifying lower bounds on prediction dimension of convex surrogates NeurIPS 2021 Calibrated Surrogate Losses for Adversarially Robust Classification COLT 2020 Convex Calibrated Surrogates for the Multi-Label F-Measure ICML 2020 Embedding Dimension of Polyhedral Losses COLT 2020 Variance-based Regularization with Convex Objectives JMLR 2019 Quantifying Learning Guarantees for Convex but Inconsistent Surrogates NeurIPS 2018 On Structured Prediction Theory with Calibrated Convex Surrogate Losses NeurIPS 2017 A Convex Surrogate Operator for General Non-Modular Loss Functions AISTATS 2016 A Greedy Homotopy Method for Regression with Nonconvex Constraints AISTATS 2015 Convex Calibrated Surrogates for Hierarchical Classification ICML 2015 Learning Submodular Losses with the Lovasz Hinge ICML 2015 On Consistent Surrogate Risk Minimization and Property Elicitation COLT 2015 Interval Insensitive Loss for Ordinal Classification ACML 2014 The Coherent Loss Function for Classification ICML 2014 Convex Calibrated Surrogates for Low-Rank Loss Matrices with Applications to Subset Ranking Losses NeurIPS 2013 Cost-sensitive Multiclass Classification Risk Bounds ICML 2013 Accuracy at the Top NeurIPS 2012 Classification Calibration Dimension for General Multiclass Losses NeurIPS 2012 On the Efficient Minimization of Classification Calibrated Surrogates NeurIPS 2008