{"total":14,"rows":[{"id":"2304.07288","title":"Cross-Entropy Loss Functions: Theoretical Analysis and Applications","created":"2023-04-14","cited_by_count":210,"area":null},{"id":"2407.13722","title":"Enhanced $H$-Consistency Bounds","created":"2024-07-18","cited_by_count":18,"area":null},{"id":"2207.08873","title":"Consistent Polyhedral Surrogates for Top-$k$ Classification and Variants","created":"2022-07-18","cited_by_count":8,"area":null},{"id":"2504.18395","title":"Three Types of Calibration with Properties and their Semantic and Formal Relationships","created":"2025-04-25","cited_by_count":5,"area":null},{"id":"2505.09432","title":"Establishing Linear Surrogate Regret Bounds for Convex Smooth Losses via Convolutional Fenchel-Young Losses","created":"2025-05-14","cited_by_count":2,"area":null},{"id":"2402.10818","title":"Trading off Consistency and Dimensionality of Convex Surrogates for the Mode","created":"2024-02-16","cited_by_count":1,"area":null},{"id":"2502.19522","title":"Contrasting Cost-Agnostic and Cost-Sensitive Losses under Limited Model Capacity via $\\mathcal H$-consistency","created":"2025-02-26","cited_by_count":1,"area":null},{"id":"2505.13760","title":"Consistency Conditions for Differentiable Surrogate Losses","created":"2025-05-19","cited_by_count":1,"area":null},{"id":"2608.08399","title":"Exact Rank and Convex Calibration Dimension Lower Bounds for the Multi-Label F1 Loss","created":"2026-08-09","cited_by_count":1,"area":null},{"id":"2312.07802","title":"Estimation of embedding vectors in high dimensions","created":"2023-12-12","cited_by_count":0,"area":null},{"id":"2505.06446","title":"Structured Prediction with Abstention via the Lov\\'asz Hinge","created":"2025-05-09","cited_by_count":0,"area":null},{"id":"2605.23017","title":"Smoothed Elicitation Complexity for Approximate $\\Gamma$-calibration of Discrete Classification Tasks","created":"2026-05-21","cited_by_count":0,"area":null},{"id":"2608.27203","title":"Common Geodesics Do Not Guarantee Fisher Consistency of the Structured SVM: Minimal Counterexamples and a Tree-Metric Classification","created":"2026-08-27","cited_by_count":0,"area":null},{"id":"2609.33472","title":"Geometric Identification in Predict-Then-Optimize Learning","created":"2026-09-27","cited_by_count":0,"area":null}],"next_cursor":null}