Examples

Learning LibAUC: More Examples

This section covers a range of applications colleccted from researchers who use LibAUC on their own projets. This section would be to help users deepen their understanding of LibAUC and its applications by providing further use cases and examples.

• Efficient Fraud Detection using Deep Boosting Decision Trees by Biao Xu, et al.
• AUC Maximization for Low-Resource Named Entity Recognition by Ngoc Dang Nguyen, et al.
• AUC-oriented Graph Neural Network for Fraud Detection by Key Laboratory of Intelligent Information Processing of CAS
• Multimodal-Medical-Diagnosis-System by ChihchengHsieh
• DeepAUC OGB Challenge by ML@UIowa
• PAS-OGB by AutoML Research
• Heterogeneous interpolation on graph by Tencent Youtu Research
• Performance or Trust? Why Not Both. Deep AUC Maximization with Self-Supervised Learning for COVID-19 Chest X-ray Classifications by National Research Council Canada
• SIIM-FISABIO-RSNA COVID-19 Detection|Kaggle by seriousran
• MIT AI Cures Challenge by TAMU & UIowa
• RSNA Brain tumor classification|Kaggle by Tharun_kumar
• RANZCR CLiP - Catheter and Line Position Challenge|Kaggle by jun2tong
• SIIM-ISIC Melanoma Classification|Kaggle by ML@UIowa
• Tabular Playground Series|Kaggle by SEJOONG KIM
• Stanford CheXpert Classification by ML@UIowa
• Evaluation of ensemble learning for disease classification on chest radiographs by Sebastian Steindl