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Learning for Tail Label Data: A Label-Specific Feature Approach.

, , and . IJCAI, page 3842-3848. ijcai.org, (2019)

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Towards Discovering What Patterns Trigger What Labels., , , and . AAAI, AAAI Press, (2012)Towards Safe Semi-Supervised Learning for Multivariate Performance Measures., , and . AAAI, page 1816-1822. AAAI Press, (2016)Risk Minimization in the Presence of Label Noise., , , and . AAAI, page 1575-1581. AAAI Press, (2016)Instance Selection Method for Improving Graph-Based Semi-supervised Learning., , and . PRICAI, volume 9810 of Lecture Notes in Computer Science, page 565-573. Springer, (2016)Towards Automated Semi-Supervised Learning., , , and . AAAI, page 4237-4244. AAAI Press, (2019)Robust Semi-supervised Representation Learning for Graph-Structured Data., , and . PAKDD (3), volume 11441 of Lecture Notes in Computer Science, page 131-143. Springer, (2019)Graph Quality Judgement: A Large Margin Expedition., , and . IJCAI, page 1725-1731. IJCAI/AAAI Press, (2016)Does Tail Label Help for Large-Scale Multi-Label Learning., and . IJCAI, page 2847-2853. ijcai.org, (2018)Partial Label Learning with Unlabeled Data., , and . IJCAI, page 3755-3761. ijcai.org, (2019)Learning for Tail Label Data: A Label-Specific Feature Approach., , and . IJCAI, page 3842-3848. ijcai.org, (2019)