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W. Philip Kegelmeyer
2010 – today
- 2012
[j10]David A. Cieslak, T. Ryan Hoens, Nitesh V. Chawla, W. Philip Kegelmeyer: Hellinger distance decision trees are robust and skew-insensitive. Data Min. Knowl. Discov. 24(1): 136-158 (2012)- [c21]Keith Stevens, W. Philip Kegelmeyer, David Andrzejewski, David Buttler: Exploring Topic Coherence over Many Models and Many Topics. EMNLP-CoNLL 2012: 952-961
- 2011
- [j9]Larry Shoemaker, Robert E. Banfield, Lawrence O. Hall, Kevin W. Bowyer, W. Philip Kegelmeyer: Detecting and ordering salient regions. Data Min. Knowl. Discov. 22(1-2): 259-290 (2011)
- [c20]Justin D. Basilico, M. Arthur Munson, Tamara G. Kolda, Kevin R. Dixon, W. Philip Kegelmeyer: COMET: A Recipe for Learning and Using Large Ensembles on Massive Data. ICDM 2011: 41-50
- [c19]Brett W. Bader, W. Philip Kegelmeyer, Peter A. Chew: Multilingual Sentiment Analysis Using Latent Semantic Indexing and Machine Learning. ICDM Workshops 2011: 45-52
- [i2]Justin D. Basilico, M. Arthur Munson, Tamara G. Kolda, Kevin R. Dixon, W. Philip Kegelmeyer: COMET: A Recipe for Learning and Using Large Ensembles on Massive Data. CoRR abs/1103.2068 (2011)
- [i1]Kevin W. Bowyer, Nitesh V. Chawla, Lawrence O. Hall, W. Philip Kegelmeyer: SMOTE: Synthetic Minority Over-sampling Technique. CoRR abs/1106.1813 (2011)
2000 – 2009
- 2009
- [c18]Michael J. Procopio, W. Philip Kegelmeyer, Gregory Z. Grudic, Jane Mulligan: Terrain Segmentation with On-Line Mixtures of Experts for Autonomous Robot Navigation. MCS 2009: 385-397
- 2008
- [j8]Larry Shoemaker, Robert E. Banfield, Lawrence O. Hall, Kevin W. Bowyer, W. Philip Kegelmeyer: Using classifier ensembles to label spatially disjoint data. Information Fusion 9(1): 120-133 (2008)
- [c17]John Nicholas Korecki, Robert E. Banfield, Larry O. Hall, Kevin W. Bowyer, W. Philip Kegelmeyer: Semi-supervised learning on large complex simulations. ICPR 2008: 1-4
- [c16]Larry Shoemaker, Robert E. Banfield, Larry O. Hall, Kevin W. Bowyer, W. Philip Kegelmeyer: Detecting and ordering salient regions for efficient browsing. ICPR 2008: 1-4
- [c15]Clayton Springer, W. Philip Kegelmeyer: Feature selection via decision tree surrogate splits. ICPR 2008: 1-5
- 2007
- [j7]Robert E. Banfield, Lawrence O. Hall, Kevin W. Bowyer, W. Philip Kegelmeyer: A Comparison of Decision Tree Ensemble Creation Techniques. IEEE Trans. Pattern Anal. Mach. Intell. 29(1): 173-180 (2007)
- [c14]Lawrence O. Hall, Robert E. Banfield, Kevin W. Bowyer, W. Philip Kegelmeyer: Boosting Lite - Handling Larger Datasets and Slower Base Classifiers. MCS 2007: 161-170
- 2006
- [c13]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. ICTAI 2006: 116-126
- 2005
- [j6]Robert E. Banfield, Lawrence O. Hall, Kevin W. Bowyer, W. Philip Kegelmeyer: Ensemble diversity measures and their application to thinning. Information Fusion 6(1): 49-62 (2005)
- [c12]Wendy S. Koegler, W. Philip Kegelmeyer: FCLib: A Library for Building Data Analysis and Data Discovery Tools. IDA 2005: 192-203
- [c11]Robert E. Banfield, Lawrence O. Hall, Kevin W. Bowyer, W. Philip Kegelmeyer: Ensembles of Classifiers from Spatially Disjoint Data. Multiple Classifier Systems 2005: 196-205
- 2004
- [j5]Nitesh V. Chawla, Lawrence O. Hall, Kevin W. Bowyer, W. Philip Kegelmeyer: Learning Ensembles from Bites: A Scalable and Accurate Approach. Journal of Machine Learning Research 5: 421-451 (2004)
- [c10]
- [c9]Robert E. Banfield, Lawrence O. Hall, Kevin W. Bowyer, Divya Bhadoria, W. Philip Kegelmeyer, Steven Eschrich: A Comparison of Ensemble Creation Techniques. Multiple Classifier Systems 2004: 223-232
- 2003
- [j4]Nitesh V. Chawla, Thomas E. Moore, Lawrence O. Hall, Kevin W. Bowyer, W. Philip Kegelmeyer, Clayton Springer: Distributed learning with bagging-like performance. Pattern Recognition Letters 24(1-3): 455-471 (2003)
- [c8]Lawrence O. Hall, Kevin W. Bowyer, Robert E. Banfield, Divya Bhadoria, W. Philip Kegelmeyer, Steven Eschrich: Comparing Pure Parallel Ensemble Creation Techniques Against Bagging. ICDM 2003: 533-536
- [c7]Robert E. Banfield, Lawrence O. Hall, Kevin W. Bowyer, W. Philip Kegelmeyer: A New Ensemble Diversity Measure Applied to Thinning Ensembles. Multiple Classifier Systems 2003: 306-316
- 2002
- [j3]Nitesh V. Chawla, Kevin W. Bowyer, Lawrence O. Hall, W. Philip Kegelmeyer: SMOTE: Synthetic Minority Over-sampling Technique. J. Artif. Intell. Res. (JAIR) 16: 321-357 (2002)
- [c6]Nitesh V. Chawla, Lawrence O. Hall, Kevin W. Bowyer, Thomas E. Moore, W. Philip Kegelmeyer: Distributed Pasting of Small Votes. Multiple Classifier Systems 2002: 52-61
- 2001
- [c5]Nitesh V. Chawla, Thomas E. Moore, Kevin W. Bowyer, Lawrence O. Hall, Clayton Springer, W. Philip Kegelmeyer: Bagging Is a Small-Data-Set Phenomenon. CVPR (2) 2001: 684-689
- [c4]Elizabeth Bradley, Nancy Collins, W. Philip Kegelmeyer: Feature Characterization in Scientific Datasets. IDA 2001: 1-12
- [c3]Nitesh V. Chawla, Thomas E. Moore, Kevin W. Bowyer, Lawrence O. Hall, Clayton Springer, W. Philip Kegelmeyer: Investigation of bagging-like effects and decision trees versus neural nets in protein secondary structure prediction. BIOKDD 2001: 50-59
1990 – 1999
- 1999
- [c2]Lawrence O. Hall, Nitesh V. Chawla, Kevin W. Bowyer, W. Philip Kegelmeyer: Learning Rules from Distributed Data. Large-Scale Parallel Data Mining 1999: 211-220
- 1997
- [j2]Mark C. Allmen, W. Philip Kegelmeyer: The computation of cloud base height from paired whole-sky imaging cameras. Mach. Vis. Appl. 9(4): 160-165 (1997)
- [j1]Kevin S. Woods, W. Philip Kegelmeyer, Kevin W. Bowyer: Combination of Multiple Classifiers Using Local Accuracy Estimates. IEEE Trans. Pattern Anal. Mach. Intell. 19(4): 405-410 (1997)
- 1996
- [c1]Kevin S. Woods, Kevin W. Bowyer, W. Philip Kegelmeyer: Combination of Multiple Classifiers Using Local Accuracy Estimates. CVPR 1996: 391-396
Coauthor Index
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last updated on 2013-04-17 21:43 CEST by the dblp team