Jianmin Wang

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Efficient similarity retrieval from large-scale multimodal database is pervasive in modern search engines and social networks. To support queries across content modalities, the system should enable cross-modal correlation and computation-efficient indexing. While hashing methods have shown great potential in achieving this goal, current attempts generally(More)
To save the labeling efforts for training a classification model, we can simultaneously adopt Active Learning (AL) to select the most informative samples for human labeling, and Semi-supervised Learning (SSL) to construct effective classifiers using a few labeled samples and a large number of unlabeled samples. Recently, using Transfer Learning (TL) to(More)
Due to the storage and retrieval efficiency, hashing has been widely applied to approximate nearest neighbor search for large-scale multimedia retrieval. Cross-modal hashing, which enables efficient retrieval of images in response to text queries or vice versa, has received increasing attention recently. Most existing work on cross-modal hashing does not(More)