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@@ -56,7 +56,7 @@ You can also download source code from [here](https://github.com/Optimization-AI
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- Optimizing <strong>AUROC</strong> loss with DenseNet121 on <strong>CheXpert</strong> [[Notebook](https://github.com/Optimization-AI/LibAUC/blob/main/examples/05_Optimizing_AUROC_Loss_with_DenseNet121_on_CheXpert.ipynb)][[Script](https://github.com/Optimization-AI/LibAUC/tree/main/examples/scripts)]
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- Optimizing <strong>AUROC</strong> loss with DenseNet121 on CIFAR100 for **Federated Learning**[[Preliminary Release](https://github.com/Optimization-AI/LibAUC/blob/main/examples/scripts/06_Optimizing_AUROC_loss_with_DenseNet121_on_CIFAR100_in_Federated_Setting_CODASCA.py)]
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- Optimizing <strong>AUROC</strong> loss with DenseNet121 on <strong>Melanoma</strong> [[Notebook](https://github.com/Optimization-AI/LibAUC/blob/main/examples/08_Optimizing_AUROC_Loss_with_DenseNet121_on_Melanoma.ipynb)][[Script](https://github.com/Optimization-AI/LibAUC/tree/main/examples/scripts)]
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- Optimizing <strong>Multi-Label AUROC</strong> loss with DenseNet121 on <strong>CheXpert</strong> [[Notebook](https://github.com/Optimization-AI/LibAUC/blob/main/examples/07_Optimizing_Multi_Label_AUROC_Loss_with_DenseNet121_on_CheXpert.ipynb)][[Script](https://github.com/Optimization-AI/LibAUC/tree/main/examples/scripts)]
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- Optimizing <strong>AUROC (Multi-Label)</strong> loss with DenseNet121 on <strong>CheXpert</strong> [[Notebook](https://github.com/Optimization-AI/LibAUC/blob/main/examples/07_Optimizing_Multi_Label_AUROC_Loss_with_DenseNet121_on_CheXpert.ipynb)][[Script](https://github.com/Optimization-AI/LibAUC/tree/main/examples/scripts)]
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