"RDA: Reciprocal Distribution Alignment for Robust Semi-supervised Learning" by Yue Duan (ECCV 2022)
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Updated
Aug 8, 2024 - Python
"RDA: Reciprocal Distribution Alignment for Robust Semi-supervised Learning" by Yue Duan (ECCV 2022)
AAAI 2021: Robustness of Accuracy Metric and its Inspirations in Learning with Noisy Labels
Principled learning method for Wasserstein distributionally robust optimization with local perturbations (ICML 2020)
Code for "Transfer Learning without Knowing: Reprogramming Black-box Machine Learning Models with Scarce Data and Limited Resources". (ICML 2020)
[Re] Can gradient clipping mitigate label noise? (ML Reproducibility Challenge 2020)
AAAI 2021: Beyond Class-Conditional Assumption: A Primary Attempt to Combat Instance-Dependent Label Noise
Source code for Self-Guided Learning to Denoise for Robust Recommendation. SIGIR 2022.
Defending graph neural networks against adversarial attacks (NeurIPS 2020)
[ICML2020] Normalized Loss Functions for Deep Learning with Noisy Labels
Official Implementation of Early-Learning Regularization Prevents Memorization of Noisy Labels
[NeurIPS 2021] WRENCH: Weak supeRvision bENCHmark
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