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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Page: 1 2 3 4 Hits 1 – 20 of 71 1 Improving BERT Model Using Contrastive Learning for Biomedical Relation Extraction ... Su, Peng; Peng, Yifan; Vijay-Shanker, K.. - : arXiv, 2021 BASE Show details 2 iTextMine: integrated text-mining system for large-scale knowledge extraction from the literature Ren, Jia; Li, Gang; Ross, Karen. - : Oxford University Press, 2018 BASE Show details 3 An Approach to Reducing Annotation Costs for BioNLP ... Bloodgood, Michael; Vijay-Shanker, K.. - : arXiv, 2014 BASE Show details 4 Taking into Account the Differences between Actively and Passively Acquired Data: The Case of Active Learning with Support Vector Machines for Imbalanced Datasets ... Bloodgood, Michael; Vijay-Shanker, K.. - : arXiv, 2014 BASE Show details 5 Rapid Adaptation of POS Tagging for Domain Specific Uses ... Miller, John E.; Bloodgood, Michael; Torii, Manabu. - : arXiv, 2014 BASE Show details 6 iSimp in BioC standard format: enhancing the interoperability of a sentence simplification system Peng, Yifan; Tudor, Catalina O.; Torii, Manabu. - : Oxford University Press, 2014 BASE Show details 7 A Method for Stopping Active Learning Based on Stabilizing Predictions and the Need for User-Adjustable Stopping ... Bloodgood, Michael; Vijay-Shanker, K. - : Digital Repository at the University of Maryland, 2009 BASE Show details 8 Taking into Account the Differences between Actively and Passively Acquired Data: The Case of Active Learning with Support Vector Machines for Imbalanced Datasets ... Bloodgood, Michael; Vijay-Shanker, K. - : Digital Repository at the University of Maryland, 2009 BASE Show details 9 A Method for Stopping Active Learning Based on Stabilizing Predictions and the Need for User-Adjustable Stopping Bloodgood, Michael; Vijay-Shanker, K. - : Association for Computational Linguistics, 2009 BASE Show details 10 Taking into Account the Differences between Actively and Passively Acquired Data: The Case of Active Learning with Support Vector Machines for Imbalanced Datasets Bloodgood, Michael; Vijay-Shanker, K. - : Association for Computational Linguistics, 2009 Abstract: Actively sampled data can have very different characteristics than passively sampled data. Therefore, it’s promising to investigate using different inference procedures during AL than are used during passive learning (PL). This general idea is explored in detail for the focused case of AL with cost-weighted SVMs for imbalanced data, a situation that arises for many HLT tasks. The key idea behind the proposed InitPA method for addressing imbalance is to base cost models during AL on an estimate of overall corpus imbalance computed via a small unbiased sample rather than the imbalance in the labeled training data, which is the leading method used during PL. Keyword: active learning; annotation bottleneck; annotation costs; artificial intelligence; asymmetric cost factors; asymmetric cost weights; binary classification; biomedical natural language processing; biomedical text processing; BioNLP; computational linguistics; computer science; corpus imbalance; cost modeling; cost models; cost-sensitive active learning; cost-sensitive learning; cost-weighted support vector machines; cost-weighted SVMs; human language technology; imbalanced data; imbalanced datasets; imbalanced learning; machine learning; natural language processing; newswire text classification; positive amplification; protein-protein interaction extraction; query learning; relation extraction; selective sampling; statistical methods; support vector machines; SVMs; text classification; text processing URL: http://hdl.handle.net/1903/15585 https://doi.org/10.13016/M2QP4K BASE Hide details 11 An Approach to Reducing Annotation Costs for BioNLP ... Bloodgood, Michael; Vijay-Shanker, K. - : Digital Repository at the University of Maryland, 2008 BASE Show details 12 An Approach to Reducing Annotation Costs for BioNLP Bloodgood, Michael; Vijay-Shanker, K. - : Association for Computational Linguistics, 2008 BASE Show details 13 Automated extraction of tree-adjoining grammars from treebanks Chen, John; Bangalore, Srinivas; Vijay-Shanker, K. In: Natural language engineering. - Cambridge : Cambridge University Press 12 (2006) 3, 251-299 BLLDB Show details 14 Rapid Adaptation of POS Tagging for Domain Specific Uses ... Miller, John; Bloodgood, Michael; Torii, Manabu. - : Digital Repository at the University of Maryland, 2006 BASE Show details 15 Rapid Adaptation of POS Tagging for Domain Specific Uses Miller, John; Bloodgood, Michael; Torii, Manabu. - : Association for Computational Linguistics, 2006 BASE Show details 16 Automated extraction of tags from the Penn Treebank Chen, John; Vijay-Shanker, K. In: New developments in parsing technology. - Dordrecht [u.a.] : Kluwer (2004), 73-89 BLLDB Show details 17 Roots, constituents, and c-command Frank, Robert; Hagstrom, Paul; Vijay-Shanker, K. In: Theoretical approaches to universals. - Amsterdam [u.a.] : Benjamins (2002), 109-137 BLLDB Show details 18 Roots, constituents, and c-command Frank, Robert; Hagstrom, Paul; Vijay-Shanker, K. In: Theoretical approaches to universals (2002), 109-139 IDS Bibliografie zur deutschen Grammatik Show details 19 Randomized rule selection in transformation-based learning : a comparative study Carberry, Sandra; Vijay-Shanker, K.; Wilson, Andrew... In: Natural language engineering. - Cambridge : Cambridge University Press 7 (2001) 2, 99-116 BLLDB Show details 20 Primitive C-command Frank, Robert; Vijay-Shanker, K. In: Syntax. - Oxford : Wiley-Blackwell 4 (2001) 3, 164-204 BLLDB Show details Page: 1 2 3 4

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