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Found 2 papers, 2 papers with code
Hierarchical Contrastive Learning for Pattern-Generalizable Image Corruption Detection
Detecting corrupted regions by learning the contrastive distinctions rather than the semantic patterns of corruptions, our model has well generalization ability across different corruption patterns.
Fed-TDA: Federated Tabular Data Augmentation on Non-IID Data
Non-independent and identically distributed (non-IID) data is a key challenge in federated learning (FL), which usually hampers the optimization convergence and the performance of FL.
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