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Data scarcity, robustness and extreme multi-label classification, and . (2019)Speeding-up One-vs-All Training for Extreme Classification via Smart Initialization., and . CoRR, (2021)Embedding Convolutions for Short Text Extreme Classification with Millions of Labels., , , and . CoRR, (2021)Explainable Publication Year Prediction of Eighteenth Century Texts with the BERT Model., , , , , , , , and . LChange@ACL, page 68-77. Association for Computational Linguistics, (2022)Using ECCO-BERT and the Historical Thesaurus of English to Explore Concepts and Agency in Historical Writing Interpreting the Eighteenth-century Luxury Debate., , , , , , , , , and 3 other author(s). DH, (2023)On empirical tradeoffs in large scale hierarchical classification., , , and . CIKM, page 2299-2302. ACM, (2012)Learning Taxonomy Adaptation in Large-scale Classification., , , , and . J. Mach. Learn. Res., (2016)Meta-classifier free negative sampling for extreme multilabel classification., and . Mach. Learn., 113 (2): 675-697 (February 2024)Bonsai: diverse and shallow trees for extreme multi-label classification., , and . Mach. Learn., 109 (11): 2099-2119 (2020)Extreme Multicore Classification., and . Mach. Learn. under Resour. Constraints Vol. 1 (1), De Gruyter, (2022)