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AUC Optimization from Multiple Unlabeled Datasets

arXiv 2305.15776 ↗First posted 25 May 2023cs.LGcited by 0

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Abstract (arXiv)

Weakly supervised learning aims to empower machine learning when the perfect supervision is unavailable, which has drawn great attention from researchers. Among various types of weak supervision, one of the most challenging cases is to learn from multiple unlabeled (U) datasets with only a little knowledge of the class priors, or Um learning for short. In this paper, we study the problem of building an AUC (area under ROC curve) optimization model from multiple unlabeled datasets, which maximizes the pairwise ranking ability of the classifier. We propose Um-AUC, an AUC optimization approach that converts the Um data into a multi-label AUC optimization problem, and can be trained efficiently. We show that the proposed Um-AUC is effective theoretically and empirically.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 22 of its 45 references that are in the map. First posted on arXiv 25 May 2023.

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22 of 45 references.

References · 22

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  12. 2013One-Pass AUC Optimizationcited by 42
10 more
  1. 2014On Learning from Label Proportionscited by 38
  2. 2021Learning with Multiclass AUC: Theory and Algorithmscited by 35
  3. 2019Learning from Label Proportions with Consistency Regularizationcited by 34
  4. 2022When AUC meets DRO: Optimizing Partial AUC for Deep Learning with Non-Convex Convergence Guaranteecited by 29
  5. 2017Semi-Supervised AUC Optimization based on Positive-Unlabeled Learningcited by 20
  6. 2020Fast Objective & Duality Gap Convergence for Non-Convex Strongly-Concave Min-Max Problems with PL Conditioncited by 19
  7. 2022Large-scale Optimization of Partial AUC in a Range of False Positive Ratescited by 15
  8. 2021Binary Classification from Multiple Unlabeled Datasets via Surrogate Set Classificationcited by 12
  9. 2023Weakly Supervised AUC Optimization: A Unified Partial AUC Approachcited by 11
  10. 2020Learning from Label Proportions: A Mutual Contamination Frameworkcited by 6

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