Publications by W. Philip Kegelmeyer

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Larry Shoemaker, Robert E. Banfield, Lawrence O. Hall, Kevin W. Bowyer and W. Philip Kegelmeyer, "Using classifier ensembles to label spatially disjoint data", Information Fusion Journal, Special Issue on Applications of Ensemble Methods, 9:1, pp. 120-133, January 2008.

Larry Shoemaker, Robert E. Banfield, Lawrence O. Hall, Kevin W. Bowyer, W. Philip Kegelmeyer, "Learning to Predict Salient Regions from Disjoint and Skewed Training Sets", in Proceedings of the 18th IEEE Conference on Tools with Artificial Intelligence (ICTAI 2006), Arlington, Virginia, USA, pp. 116-123, 2006.

Robert E. Banfield, Lawrence O. Hall, Kevin W. Bowyer, W. Philip Kegelmeyer, "A Comparison of Decision Tree Ensemble Creation Techniques", IEEE Transactions on Pattern Analysis and Machine Intelligence, v. 29, no. 1, pp 173-180, January 2007.Appendix.

"Ensembles of Classifiers from Spatially Disjoint Data", Robert E. Banfield, Lawrence O. Hall, Kevin W. Bowyer, W. Philip Kegelmeyer, The Sixth International Conference on Multiple Classifier Systems, Monterey, CA, pp. 196-205, June 2005.

"Ensemble Diversity Measures and their Application to Thinning", Robert E. Banfield, Lawrence O. Hall, Kevin W. Bowyer, W. Philip Kegelmeyer, Information Fusion Journal, 6:1, pp49-62, March 2005.

"A Comparison of Ensemble Creation Techniques", Robert E. Banfield, Lawrence O. Hall, Kevin W. Bowyer, Divya Bhadoria, W. Philip Kegelmeyer and Steven Eschrich, The Fifth International Conference on Multiple Classifier Systems, Cagliari, Italy, June, 2004. [Slides]

"Learning ensembles from bites: A scalable and accurate approach", Nitesh V. Chawla, Lawrence O. Hall, Kevin W. Bowyer, W. Philip Kegelmeyer, Journal of Machine Learning Research, 2003

"Comparing Pure Parallel Ensemble Creation Techniques Against Bagging" Lawrence O. Hall, KevinW. Bowyer, Robert E. Banfield, Divya Bhadoria, W. Philip Kegelmeyer and Steven Eschrich, The Third IEEE International Conference on Data Mining, Melbourne, Florida, pp. 533-536, November, 2003.

"A New Ensemble Diversity Measure Applied to Thinning Ensembles" Robert E. Banfield, Lawrence O. Hall, Kevin W. Bowyer, W. Philip Kegelmeyer, International Workshop on Multiple Classifier Systems, pp. 306 - 316, Surrey, UK, June, 2003.

"SMOTE: Synthetic Minority Over-sampling technique", Nitesh Chawla, Kevin Bowyer, Lawrence Hall, Philip Kegelmeyer, Journal of Artificial Intelligence Research , Volume 16, 321 -- 357, 2002. (This paper is available online from the JAIR site.)

"Distributed Pasting of Small Votes" Nitesh V. Chawla, Lawrence O. Hall, Kevin W. Bowyer, Thomas E. Moore, W. Philip Kegelmeyer. International Workshop on Multiple Classifier Systems, 2002 .

"Distributed learning with bagging-like performance", Nitesh V. Chawla, Thomas E. Moore, Lawrence O. Hall, Kevin W. Bowyer, W. Philip Kegelmeyer, Clayton Springer. Published in Pattern Recognition Letters, Vol. 24 (1-3) (2003) pp. 455-471

"Extreme Data Mining: What to do with a flood of training data?" Nitesh  Chawla, Lawrence Hall, Kevin Bowyer, Thomas Moore, Clayton Springer, Philip Kegelmeyer, Invited Talk, Conference of Institute of Operations Research and Management Sciences, (INFORMS) , 2001 .

"Bagging is a Small-Data-Set phenomenon" Nitesh Chawla, Thomas  Moore, Kevin Bowyer, Lawrence Hall, Clayton Springer, Philip Kegelmeyer. International Conference on Computer Vision and Pattern Recognition (CVPR), 2001

"Investigation of bagging-like effects and decision trees versus neural nets in protein secondary structure prediction", Nitesh  Chawla, Thomas Moore, Kevin Bowyer, Lawrence Hall, Clayton Springer, Philip Kegelmeyer. Workshop on Data Mining in Bioinformatics, Knowledge Discovery and Data Mining (KDD), 2001

"SMOTE: Synthetic Minority Over-sampling technique", Nitesh Chawla, Kevin Bowyer, Lawrence Hall, Philip Kegelmeyer, International Conference on Knowledge Based Computer Systems , 2000. 

Distributed Learning on Very Large Data Sets, L.O. Hall, K.W. Bowyer, W.P. Kegelmeyer, T.E. Moore and C. Chao, Workshop on Distributed and Parallel Knowledge Discovery, International Conference Knowledge Discovery and Data Mining (KDD), 2000.

"A Parallel Decision Tree Builder for Mining Very Large Visualization DataSets", Bowyer, Hall, Chawla, Moore, Kegelmeyer. IEEE International Conference on Systems, Man, and Cybernetics, 2000.

"AVATAR -- Adaptive Visualization Aid for Touring and Recovery," Lawrence O. Hall, Kevein W. Bowyer, Nitesh V. Chawla, Thomas E. Moore, W. Philip Kegelmeyer, Sandia - Report, SAND2000-8203, Sandia National Labs , 2000.

"Learning rules from distributed data," Lawrence O. Hall, Nitesh Chawla, Kevin W. Bowyer, W. Philip Kegelmeyer, Large-Scale Parallel KDD Systems, International Conference of Knowledge Discovery and Data Mining . Lecture Notes in Computer Science,Springer Verlag, 1999.