Temporally and Distributionally Robust Optimization for Cold-start Recommendation (AAAI'24)
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Updated
Mar 28, 2024 - Python
Temporally and Distributionally Robust Optimization for Cold-start Recommendation (AAAI'24)
Implementation of paper: Equivariant Learning for Out-of-Distribution Cold-start Recommendation. (backbone model CLCRec) (MM'23)
Robust and Highly Sensitive Covariate Shift Detection using XGBoost
Code for the Conditional Mutual Information-Debiasing (CMID) method.
Code for "Improving Stain Invariance of CNNs for Segmentation by Fusing Channel Attention and Domain-Adversarial Training"
Implementation codes for NeurIPS23 paper "Spectral Invariant Learning for Dynamic Graphs under Distribution Shifts"
Coping with Label Shift via Distributionally Robust Optimisation
"RDA: Reciprocal Distribution Alignment for Robust Semi-supervised Learning" by Yue Duan (ECCV 2022)
Code accompanying our paper titled Online Label Shift: Optimal Dynamic Regret meets Practical Algorithms
Quilt: Robust Data Segment Selection against Concept Drifts (AAAI 2024)
Official implementation of the Fréchet Radiomics Distance.
A Python Library for Biquality Learning
[ICLR 2023] Official Tensorflow implementation of "Distributionally Robust Post-hoc Classifiers under Prior Shifts"
[NeurIPS 2023 (Spotlight)] Uncovering the Hidden Dynamics of Video Self-supervised Learning under Distribution Shifts
NeurIPS22 "RankFeat: Rank-1 Feature Removal for Out-of-distribution Detection"
A systematic approach to class distribution mismatch in semi-supervised learning using deep dataset dissimilarity measures
Global-Local Regularization Via Distributional Robustness (AISTATS 2023)
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