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All-in Text: Learning Document, Label, and Word Representations Jointly.

, , and . AAAI, page 1948-1954. AAAI Press, (2016)

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Predicting Unseen Labels Using Label Hierarchies in Large-Scale Multi-label Learning., , , and . ECML/PKDD (1), volume 9284 of Lecture Notes in Computer Science, page 102-118. Springer, (2015)Scalable and Robust Self-Learning for Skill Routing in Large-Scale Conversational AI Systems., , , , and . NAACL-HLT (Industry Papers), page 1-8. Association for Computational Linguistics, (2022)Maximizing Subset Accuracy with Recurrent Neural Networks in Multi-label Classification., , , and . NIPS, page 5413-5423. (2017)Using semantic similarity for multi-label zero-shot classification of text documents., , , and . ESANN, (2016)All-in Text: Learning Document, Label, and Word Representations Jointly., , and . AAAI, page 1948-1954. AAAI Press, (2016)Learning Context-dependent Label Permutations for Multi-label Classification., , , , , and . ICML, volume 97 of Proceedings of Machine Learning Research, page 4733-4742. PMLR, (2019)On the Importance of a Hierarchy for Learning Continuous Vector Representations of a Label Space., and . ICLR (Workshop), (2015)Medical Concept Embeddings via Labeled Background Corpora., , and . LREC, European Language Resources Association (ELRA), (2016)Weakly Supervised Referring Image Segmentation with Intra-Chunk and Inter-Chunk Consistency., , , , , and . ICCV, page 21813-21824. IEEE, (2023)Improve Sentiment Analysis of Citations with Author Modelling., , and . WASSA@NAACL-HLT, page 122-127. The Association for Computer Linguistics, (2016)