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A Robust Ranking Methodology based on Diverse Calibration of AdaBoost

, , , and . Proceedings of the ECML/PKDD 2011, (2011)

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Few Shot Rationale Generation using Self-Training with Dual Teachers., , , , and . ACL (Findings), page 4825-4838. Association for Computational Linguistics, (2023)Hedge Classification in Biomedical Texts with a Weakly Supervised Selection of Keywords.. ACL, page 281-289. The Association for Computer Linguistics, (2008)A Robust Ranking Methodology Based on Diverse Calibration of AdaBoost., , , and . ECML/PKDD (1), volume 6911 of Lecture Notes in Computer Science, page 263-279. Springer, (2011)Named Entity Recognition for Hungarian Using Various Machine Learning Algorithms., , and . Acta Cybern., 17 (3): 633-646 (2006)Learning to Rank Lexical Substitutions., , and . EMNLP, page 1926-1932. ACL, (2013)Intelligent Forecast with Dimension Reduction., and . WSC, volume 34 of Advances in Soft Computing, page 279-292. Springer, (2004)A highly accurate Named Entity corpus for Hungarian., , , , and . LREC, page 1957-1960. European Language Resources Association (ELRA), (2006)Exploring ways beyond the simple supervised learning approach for biological event extraction., , , and . BioNLP@HLT-NAACL (Shared Task), page 137-140. Association for Computational Linguistics, (2009)The CoNLL-2010 Shared Task: Learning to Detect Hedges and their Scope in Natural Language Text., , , , and . CoNLL Shared Task, page 1-12. ACL, (2010)Web-Based Lemmatisation of Named Entities., , , , , and . TSD, volume 5246 of Lecture Notes in Computer Science, page 53-60. Springer, (2008)