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Mmr-based active machine learning for bio named entity recognition. In HLT/NAACL

Annotated

  1. James Active Learning with Statistical Models – David A. Cohn, Zoubin Ghahramani, Michael I. Jordan
  2. Marc A South African Case Study – Kato Ronald and Etienne Barnard, 2006
  3. Kevin Applied Statistical Decision Theory – Raiffa, H. and Schlaiffer, R, 1967.
  4. Peter Arabic Tokenization, POS Tagging and Morphological_Disambiguation – Nizar Habash, Owen Ranbow ACL 2005
  5. Peter Morphological Features Help POS Tagging of Unknown Words Across Language Varieites – Huihsin Tseng, Daniel Jurafsky, Christopher Manning ACL SIGHAN 2005
  6. Peter Arabic Part-of-speech Tagger – Shereen Khoja
  7. Peter Tagset Design and Inflected Languages – David Elworthy 1995

Unclaimed

Part-of-Speech Tagging

  1. Probabilistic Models for Segmenting Labeling Sequence Data – John Lafferty, Andrew McCallum, Fernando Pereira

Active Learning

  1. Selective Sampling Using the Query by Committee Algorithm – Yoav Freund, H. Sebastian Seung, Eli Shamir Naftali Tishby
  2. Does Active Learning Help Automatic Dialog Act Tagging in Meeting Data” – Anand Venkataraman, Yang Liu, Elizabeth Shriberg, Andreas Stolcke
  3. Combining active and semi-supervised learning for spoken language understanding,” G. Tur, D. Tur, and R.E. Schapire, Speech Communication, vol. 45, pp. 171-186, 2005.
  4. “Mixed-Initiative Development of Language Processing Systems” – David Day, John Aberdeen, Lynette Hirschman, Robyn Kozierok, Patricia Robinson and Marc Vilain ://www.mitre.org/tech/alembic-workbench/ANLP97-bigger.html
  5. “Toward Optimal Active Learning through Sampling Estimation of Error Reduction” – Nichols Roy, Andrew McCallum
  6. “Active Learning for Statistical Natural Language Parsing” – Min Tang, Xiaoqiang Luo, Salim Roukos
  7. Query by Uncertainty. Lewis & Catleett, 1994
  8. Schohn & Cohn, 2000
  9. Pierce & Cardie, 2003
  10. G. Lucarelli and I. Androutsopoulos, “A Greek Named-Entity Recognizer that Uses Support Vector Machines and Active Learning”. In Proceedings of the 4th Hellenic Conference on Artificial Intelligence (SETN 2006), Heraklion, Greece, 2006.
  11. MULTI-CRITERIA-BASED ACTIVE LEARNING FOR NAMED ENTITY RECOGNITION. Dan SHEN, Jie ZHANG, Jian SU, Guodong ZHOU and Chew-Lim TAN. ACL 2004.
  12. S. Tong and D. Koller. 2000. Support Vector Machine Active Learning with Applications to Text Classification. In Proc. of ICML, pp. 999-1006.
  13. A. McCallum and K. Nigam.1998. Employing EM and pool-based active learning for text classification. In Proc. of ICML.
  14. A Weakly Supervised Learning Approach for Spoken Language Understanding

Wei-Lin Wu, Ru-Zhan Lu, Jian-Yong Duan, Hui Liu, Feng Gao, Yu-Quan Chen. EMNLP 2006.

  1. Cohn, D. A., Ghahramani, Z., & Jordan, M. I. (1996). Active learning with statistical models. Journal of Artificial Intelligence Research, 4, 129–145.(“Statistically Optimal”)
  2. Whitehead, 1991 “Whitehead [Whi91] showed that random exploration in a deterministic world was yields a learning time that is exponential in the number of states. Thrun [Thr92] showed that directed exploration can learn in time that is polynomial in the number of states for deterministic environments.”
  3. Linden & Weber, 1993
  4. Schmidhuber \& Storch, 1993
  5. Query by Uncertainty or QBU (Thrun \& Moller, 1992)
  6. Theory of optimal experiments V.V. Fedorov 1972 Academic press
  7. On a measure of the information provided by an experiment', D.V.Lindley 1956 Ann. Math. Statist. 27, 986-1005

Claimed

  1. Eric Active Learning for Natural Language Parsing Information Extraction – Cynthia A. Thompson, Mary Elaine Califf, Raymond J. Mooney
  2. James Selective Sampling In Natural Language Learning – Ido Dagan, Sean P. Engelson
  3. James Committee-Based Sample Selection for Probabilistic Classifiers – Shlomo Argamon-Engelson, Ido Dagan
  4. James Objective Functions and Algorithms – Brigham Anderson, Andrew Moore
  5. George Sequence Selection for Active Learning – Brigham Anderson, Sajid Siddiqi, Andrew Moore
  6. George Query by Committee – H. S. Seung, M. Opper, H. Sompolinsky
  7. Kevin Part-Of-Speech Tagging Using A Variable Memory Markov Model – Hinrich Schuetze, Yoram Singer
  8. Peter Improving Generalization With Active Learning – D A. Cohn, L. Atlas, R. Ladner
  9. Deryle Combining Linguistic Knowledge Statistical Learning in French Part-of-Spreech Tagging – Evelyne Tzoukermann, Dragomir R. Radev, William A. Gale
  10. Deryle A Memory-Based Approach to Learning Shallow Natural Language Patterns – Shlomo Argamon, Ido Dagan, Yuval Krymolowski
nlp-private/bibliography.txt · Last modified: 2015/04/22 20:45 by ryancha
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