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Area under the ROC curve, a.k.a.
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A Simple Generalisation of the Area Under the ROC Curve for Multiple Class Classification Problems
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Using the Nyström method to speed up kernel machines. In Proceedings of the 14th annual conference on neural information processing systems . 682–688
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Stability and generalization
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SMOTE: Synthetic Minority over-Sampling Technique
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CheXclusion: Fairness gaps in deep chest X-ray classifiers
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Optimizing Classifier Performance via an Approximation to the Wilcoxon-Mann-Whitney Statistic. In Proceedings of ICML . 848–855
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Optimising area under the ROC curve using gradient descent. In Proceedings of the twenty-first international conference on Machine learning . ACM, 49
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Support vector machines and area under ROC curves
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Active Learning to Maximize Area Under the ROC Curve. In Sixth International Conference on Data Mining (ICDM’06) . 149–158
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Asirra: A CAPTCHA that Exploits Interest-Aligned Manual Image Categorization. In Proceedings of 14th ACM Conference on Computer and Communications Security (CCS)
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Boosting the Area under the ROC Curve. In Advances in Neural Information Processing Systems , J. Platt, D. Koller, Y. Singer, and S. Roweis (Eds.), Vol. 20. Curran Associates, Inc
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Hinge Rank Loss and the Area Under the ROC Curve. In ECML
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Efficient AUC Maximization with Regularized Least-Squares. In SCAI
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Asymmetric Support Vector Machines: Low False-Positive Learning under the User Tolerance. In Proceedings of the 14th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (Las Vegas, Nevada, USA) (KDD ’08) . Association for Computing Machinery, 749–757
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Learning Multiple Layers of Features from Tiny Images
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Credit scoring models with auc maximization based on weighted SVM
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Identifying suspicious URLs: an application of large-scale online learning. In Proceedings of the 26th annual international conference on machine learning . 681–688
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SNAP: Fault tolerant event location estimation in sensor networks using binary data
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Robust Stochastic Approximation Approach to Stochastic Programming
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The P-Norm Push: A Simple Convex Ranking Algorithm that Concentrates at the Top of the List
Cynthia Rudin. 2009 · 2009
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Credit Scoring Models with AUC Maximization Based on Weighted SVM
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Fairness in Machine Learning: A Survey
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AUC Maximization Linear Classifier Based on Active Learning and Its Application
Guang Han and Chunxia Zhao. 2010 · 2010
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A boosting method for maximizing the partial area under the ROC curve
Osamu Komori and Shinto Eguchi. 2010 · 2010
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Partial AUC for differentiated gene detection. In 2010 IEEE International Conference on BioInformatics and BioEngineering . IEEE, 310–311
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Evolving Neural Networks with Maximum AUC for Imbalanced Data Classification. In Proceedings of the 5th International Conference on Hybrid Artificial Intelligence Systems - Volume Part I (San Sebastián, Spain) (HAIS’10) . Springer-Verlag, Berlin, Heidelberg, 335–342
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MoCo Pretraining Improves Representation and Transferability of Chest X-ray Models
Hari Sowrirajan, Jingbo Yang, Andrew Y. Ng, and Pranav Rajpurkar. 2020 · 2010
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Contrastive Learning of Medical Visual Representations from Paired Images and Text
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The Infinite Push: A New Support Vector Ranking Algorithm that Directly Optimizes Accuracy at the Absolute Top of the List. In SDM
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An Analysis of Single-Layer Networks in Unsupervised Feature Learning. In Proceedings of the Fourteenth International Conference on Artificial Intelligence and Statistics (Proceedings of Machine Learning Research, Vol. 15) , Geoffrey Gordon, David Dunson, and Miroslav Dudík (Eds.). PMLR, Fort Lauderdale, FL, USA, 215–223
Adam Coates, Andrew Ng, and Honglak Lee. 2011 · 2011
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Adaptive subgradient methods for online learning and stochastic optimization
John Duchi, Elad Hazan, and Yoram Singer. 2011 · 2011
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Partial AUC maximization in a linear combination of dichotomizers
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Online learning and online convex optimization
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An introduction to manifolds. Second
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A Survey on ROC-based Ordinal Regression
Willem Waegeman and Bernard De Baets. 2011 · 2011
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Marker selection via maximizing the partial area under the ROC curve of linear risk scores
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Online AUC Maximization. In ICML . 233–240
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Gowtham Bellala, Jason Stanley, Clayton Scott, and Suresh K. Bhavnani. 2012 · 2012
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WILDS: A Benchmark of in-the-Wild Distribution Shifts
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Fairness and Machine Learning
Solon Barocas, Moritz Hardt, and Arvind Narayanan. 2019 · 2019
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Nuanced metrics for measuring unintended bias with real data for text classification. In Companion proceedings of the 2019 world wide web conference . 491–500
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Two-player games for efficient non-convex constrained optimization. In Algorithmic Learning Theory . PMLR, 300–332
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Momentum-based variance reduction in non-convex SGD. In Advances in Neural Information Processing Systems . 15210–15219
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Stochastic Model-Based Minimization of Weakly Convex Functions
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Sparse Support Vector Infinite Push. In ICML
Alain Rakotomamonjy. 2012 · 2012
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An Extension of the Receiver Operating Characteristic Curve and AUC-Optimal Classification
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Zhuoning Yuan, Yan Yan, Milan Sonka, and Tianbao Yang. 2020 · 2012
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Smoothing multivariate performance measures
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Dissecting android malware: Characterization and evolution. In 2012 IEEE symposium on security and privacy . IEEE, 95–109
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One-pass AUC optimization. In International conference on machine learning . 906–914
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Partial AUC maximization for essential gene prediction using genetic algorithms
Kyu-Baek Hwang, Beom-Yong Ha, Sanghun Ju, and Sangsoo Kim. 2013 · 2013
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Scalable and efficient pairwise learning to achieve statistical accuracy. In Proceedings of the AAAI Conference on Artificial Intelligence , Vol. 33. 3697–3704
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AUC-MF: Point of Interest Recommendation with AUC Maximization. In 2019 IEEE 35th International Conference on Data Engineering (ICDE) . 1558–1561
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AUC-oriented Graph Neural Network for Fraud Detection. In Proceedings of the ACM Web Conference 2022 . 1311–1321
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Compositional Training for End-to-End Deep AUC Maximization. In International Conference on Learning Representations
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