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General Item Representation Learning for Cold-start Content Recommendations
Cold-start item recommendation is a long-standing challenge in recommendation systems.
Modality-Aware Representation Learning for Zero-shot Sketch-based Image Retrieval
Zero-shot learning offers an efficient solution for a machine learning model to treat unseen categories, avoiding exhaustive data collection.
Unsupervised Model Drift Estimation with Batch Normalization Statistics for Dataset Shift Detection and Model Selection
While many real-world data streams imply that they change frequently in a nonstationary way, most of deep learning methods optimize neural networks on training data, and this leads to severe performance degradation when dataset shift happens.
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