Estimating accuracy from unlabeled data

Uncertainty in Artificial Intelligence - Proceedings of the 30th Conference, UAI 2014

Volumn , Issue , 2014, Pages 682-691

  Platanios, Emmanouil Antonios ^a   Blum, Avrim ^a   Mitchell, Tom ^a  

^a Machine Learning Department Carnegie Mellon University ^*  (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE; VIRTUAL REALITY;

AUTONOMOUS LEARNING; DATA DISTRIBUTION; ERROR DEPENDENCY; ERROR RATE; LABELED DATA; MULTIPLE FUNCTION; TEXT CORPORA; UNLABELED DATA;

ERRORS;

EID: 84923272739     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (13)

1. Maria-Florina Balcan, Avrim Blum, and Yishay Mansour. Exploiting Ontology Structures and Unlabeled Data for Learning. International Conference on Machine Learning, pages 1112-1120, 2013.
2. Yoshua Bengio and Nicolas Chapados. Extensions to Metric-Based Model Selection. Journal of Machine Learning Research, 3:1209-1227, March 2003.
3. Avrim Blum and Tom Mitchell. Combining labeled and unlabeled data with co-training. In Proceedings of the Eleventh Annual Conference on Computational Learning Theory, COLT' 98, pages 92-100, 1998. doi: 10.1145/279943.279962.
4. Andrew Carlson, Burr Settles, Justin Betteridge, Bryan Kisiel, Estevam R Hruschka Jr, and TomMMitchell. Toward an Architecture for Never-Ending Language Learning. In Conference on Artificial Intelligence (AAAI), pages 1-8, 2010.
5. Ming-Wei Chang, Lev Ratinov, and Dan Roth. Guiding Semi-Supervision with Constraint-Driven Learning. In Annual Meeting of the Association of Computational Linguistics, pages 280-287, Prague, Czech Republic, June 2007.
6. Michael Collins and Yoram Singer. Unsupervised Models for Named Entity Classification. In Joint Conference on Empirical Methods in Natural Language Processing and Very Large Corpora, pages 1-11, 1999.
7. Sanjoy Dasgupta, Michael L Littman, and David McAllester. PAC Generalization Bounds for Co-training. In Neural Information Processing Systems, pages 375-382, 2001.
8. Pinar Donmez, Guy Lebanon, and Krishnakumar Balasubramanian. Unsupervised Supervised Learning I: Estimating Classification and Regression Errors without Labels. Journal of Machine Learning Research, 11:1323-1351, April 2010.
9. Omid Madani, David M Pennock, and Gary W Flake. Co-Validation: Using Model Disagreement on Unlabeled Data to Validate Classification Algorithms. In Neural Information Processing Systems, pages 1-8, 2004.
10. Fabio Parisi, Francesco Strino, Boaz Nadler, and Yuval Kluger. Ranking and combining multiple predictors without labeled data. Proceedings of the National Academy of Sciences, pages 1-28, January 2014.
11. J.K. Rowling. Harry Potter and the Sorcerer's Stone. Harry Potter US. Pottermore Limited, 2012. ISBN 9781781100271.
12. Dale Schuurmans, Finnegan Southey, Dana Wilkinson, and Yuhong Guo. Metric-Based Approaches for Semi-Supervised Regression and Classification. In Semi-Supervised Learning, pages 1-31. 2006.
13. LeilaWehbe, Brian Murphy, Partha Talukdar, Alona Fyshe, Aaditya Ramdas, and Tom Mitchell. Predicting brain activity during story processing. in review, 2014.