This is a fairly complete list of publications by Charles Parker with linked copies where possible, and BibTeX references in case you would like to reference my illustrious body of work. You can also download my full CV for more information about me.

[1] Charles Parker. On Measuring the Performance of Binary Classifiers. Knowledge and Information Systems, 35:131--152, 2013. [ bib | DOI ]
[2] X. Shelley Zhang, S. Yoon, P. DiBona, D. S. Appling, L. Ding, J. R. Doppa, D. Greeny, J. K. Guo, U. Kuter, G. Levine, R. L. MacTavish, D. McFarlane, J. R. Michaelis, Hala Mostafa, S. Ontañón, C. Parker, J. Radhakrishnan, A. Rebguns, B. Shrestha, Z. Song, E. B. Trewhitt, Huzaifa Zafar, Chongjie Zhang, Daniel Corkill, G. DeJong, T. G. Dietterich, S. Kambhampati, and Victor Lesser. An Ensemble Architecture for Learning Complex Problem-Solving Techniques from Demonstration. ACM Transactions on Intelligent Systems and Technology (TIST), 4(3):75:1--75:38, 2012. [ bib | http ]
[3] Charles Parker. An analysis of performance measures for binary classification. In The International Conference on Data Mining, pages 517--526, Vancouver, Canada, December 2011. [ bib | .pdf ]
[4] Charles Parker, Dhiraj Joshi, Phoury Lei, and Jiebo Luo. Finding geographically representative music via social media. In Proceedings of the First International ACM Workshop on Music Information Retrieval with User-centered and Multimodal Strategies, pages 27--32, November 2011. [ bib ]
[5] Charles Parker. Performance measure choices for evaluating binary classifiers. Technical Report 345598M, Eastman Kodak Company, Rochester, NY, January 2011. [ bib ]
[6] Charles Parker. An exploration of semantic audio classification. Technical Report 345596K, Eastman Kodak Company, Rochester, NY, December 2010. [ bib ]
[7] Charles Parker. Anchor point selection by KL-divergence. In WNYIPW '10: The Western New York Image Processing Workshop, Rochester, NY, November 2010. [ bib | .pdf ]
[8] Charles Parker. An empirical study of feature extraction methods for audio classification. In ICPR '10: The Twentieth International Conference on Pattern Recognition, pages 4593--4596, Istanbul, Turkey, August 2010. [ bib | .pdf ]
[9] Charles Parker and Paul Messier. Automating art print authentication using metric learning. In IAAI '09: The Twenty-First Innovative Applications of Artificial Intelligence Conference, Pasadena, CA, July 2009. [ bib | .pdf ]
[10] X. Shelley Zhang, S. Yoon, P. DiBona, D. S. Appling, L. Ding, J. R. Doppa, D. Greeny, J. K. Guo, U. Kuter, G. Levine, R. L. MacTavish, D. McFarlane, J. R. Michaelis, Hala Mostafa, S. Ontañón, C. Parker, J. Radhakrishnan, A. Rebguns, B. Shrestha, Z. Song, E. B. Trewhitt, Huzaifa Zafar, Chongjie Zhang, Daniel Corkill, G. DeJong, T. G. Dietterich, S. Kambhampati, and Victor Lesser. An ensemble learning and problem solving architecture for airspace management. In IAAI '09: The Twenty-First Innovative Applications of Artificial Intelligence Conference, pages 203--210, Pasadena, CA, July 2009. [ bib | .pdf ]
[11] Charles Parker. An analysis of Kodak nexpress failure data. Technical Report 344794L, Eastman Kodak Company, Rochester, NY, December 2008. [ bib ]
[12] Charles Parker. Structured Gradient Boosting. PhD thesis, Oregon State Unversity, Corvallis, OR, August 2007. [ bib | .pdf ]
[13] Charles Parker, Prasad Tadepalli, Weng-Keen Wong, Thomas Dietterich, and Alan Fern. Learning from demonstrations via structured prediction. In AAAI '07 Workshop on Acquiring Planning Knowledge via Demonstration, Vancouver, BC, Canada, July 2007. [ bib | .pdf ]
[14] Charles Parker, Alan Fern, and Prasad Tadepalli. Learning for efficient retrieval of structured data with noisy queries. In ICML '07: The Twenty-Fourth International Conference on Machine Learning, pages 729--736, Corvallis, OR, June 2007. [ bib | .pdf ]
[15] Charles Parker, Alan Fern, and Prasad Tadepalli. Gradient boosting for sequence alignment. In AAAI '06: The Twenty-First National Conference on Artificial Intelligence, pages 452--457, Boston, MA, July 2006. [ bib | .pdf ]
[16] Charles Parker. Applications of binary classification and adaptive boosting to the query-by-humming problem. In International Symposium on Music Information Retrieval, pages 245--251, London, England, September 2005. [ bib | .pdf ]
[17] Charles Parker. Examining synthetic databases in melodic retrieval testing. In International Conference on Computer Music, Miami, FL, November 2004. [ bib | .pdf ]
[18] Charles Parker. A fast tree-based method for melodic retrieval. In ACM Joint International Conference on Digital Libraries, Tucson, AZ, June 2004. [ bib | .pdf ]
[19] Charles Parker. Towards intelligent string matching in query-by-humming systems. In IEEE International Conference on Multimedia and Expo, pages 25--28, Baltimore, MD, June 2003. [ bib | .pdf ]

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