Nitesh V. Chawla

	2009
42		Olufemi A. Omitaomu, Auroop R. Ganguly, João Gama, Ranga Raju Vatsavai, Nitesh V. Chawla, Mohamed Medhat Gaber: Proceedings of the Third International Workshop on Knowledge Discovery from Sensor Data, Paris, France, June 28, 2009 ACM 2009
41		Karsten Steinhaeuser, Nitesh V. Chawla, Auroop R. Ganguly: An exploration of climate data using complex networks. KDD Workshop on Knowledge Discovery from Sensor Data 2009: 23-31
40		Sean McRoskey, James Notwell, Nitesh V. Chawla, Christian Poellabauer: Mining in a mobile environment. KDD Workshop on Knowledge Discovery from Sensor Data 2009: 56-60
39		David A. Cieslak, Nitesh V. Chawla: A framework for monitoring classifiers' performance: when and why failure occurs? Knowl. Inf. Syst. 18(1): 83-108 (2009)
	2008
38		Darcy A. Davis, Nitesh V. Chawla, Nicholas Blumm, Nicholas Christakis, Albert-László Barabási: Predicting individual disease risk based on medical history. CIKM 2008: 769-778
37		David A. Cieslak, Nitesh V. Chawla: Learning Decision Trees for Unbalanced Data. ECML/PKDD (1) 2008: 241-256
36		David A. Cieslak, Nitesh V. Chawla, Douglas Thain: Troubleshooting thousands of jobs on production grids using data mining techniques. GRID 2008: 217-224
35		David A. Cieslak, Nitesh V. Chawla: Start Globally, Optimize Locally, Predict Globally: Improving Performance on Imbalanced Data. ICDM 2008: 143-152
34		Christopher Moretti, Karsten Steinhaeuser, Douglas Thain, Nitesh V. Chawla: Scaling up Classifiers to Cloud Computers. ICDM 2008: 472-481
33		Nitesh V. Chawla, Douglas Thain, Ryan Lichtenwalter, David A. Cieslak: Data mining on the grid for the grid. IPDPS 2008: 1-5
32		David A. Cieslak, Nitesh V. Chawla: Analyzing PETs on Imbalanced Datasets When Training and Testing Class Distributions Differ. PAKDD 2008: 519-526
31		Nitesh V. Chawla, David A. Cieslak, Lawrence O. Hall, Ajay Joshi: Automatically countering imbalance and its empirical relationship to cost. Data Min. Knowl. Discov. 17(2): 225-252 (2008)
30		Ranga Raju Vatsavai, Olufemi A. Omitaomu, Joao Gama, Nitesh V. Chawla, Mohamed Medhat Gaber, Auroop R. Ganguly: Knowledge discovery from sensor data (SensorKDD). SIGKDD Explorations 10(2): 68-73 (2008)
29		Qi Liao, David A. Cieslak, Aaron Striegel, Nitesh V. Chawla: Using selective, short-term memory to improve resilience against DDoS exhaustion attacks. Security and Communication Networks 1(4): 287-299 (2008)
	2007
28		Nitesh V. Chawla, Kevin W. Bowyer: Actively Exploring Creation of Face Space(s) for Improved Face Recognition. AAAI 2007: 809-814
27		Tanu Malik, Randal C. Burns, Nitesh V. Chawla: A Black-Box Approach to Query Cardinality Estimation. CIDR 2007: 56-67
26		David A. Cieslak, Nitesh V. Chawla: Detecting Fractures in Classifier Performance. ICDM 2007: 123-132
25		Gregory R. Madey, Albert-László Barabási, Nitesh V. Chawla, Marta Gonzalez, David Hachen, Brett Lantz, Alec Pawling, Timothy W. Schoenharl, Gábor Szabó, Pu Wang, Ping Yan: Enhanced Situational Awareness: Application of DDDAS Concepts to Emergency and Disaster Management. International Conference on Computational Science (1) 2007: 1090-1097
24		Nitesh V. Chawla, Jared Sylvester: Exploiting Diversity in Ensembles: Improving the Performance on Unbalanced Datasets. MCS 2007: 397-406
23		Michael J. Chapple, Nitesh V. Chawla, Aaron Striegel: Authentication anomaly detection: a case study on a virtual private network. MineNet 2007: 17-22
	2006
22		David A. Cieslak, Douglas Thain, Nitesh V. Chawla: Troubleshooting Distributed Systems via Data Mining. HPDC 2006: 309-312
21		Jared Sylvester, Nitesh V. Chawla: Evolutionary Ensemble Creation and Thinning. IJCNN 2006: 5148-5155
20		Alec Pawling, Nitesh V. Chawla, Amitabh Chaudhary: Evaluation of Summarization Schemes for Learning in Streams. PKDD 2006: 347-358
19		Tanu Malik, Randal C. Burns, Nitesh V. Chawla, Alexander S. Szalay: Data management and query - Estimating query result sizes for proxy caching in scientific database federations. SC 2006: 102
18		Yang Liu, Nitesh V. Chawla, Mary P. Harper, Elizabeth Shriberg, Andreas Stolcke: A study in machine learning from imbalanced data for sentence boundary detection in speech. Computer Speech & Language 20(4): 468-494 (2006)
	2005
17		Nitesh V. Chawla, Kevin W. Bowyer: Random Subspaces and Subsampling for 2-D Face Recognition. CVPR (2) 2005: 582-589
16		Nitesh V. Chawla: Many Are Better Than One: Improving Probabilistic Estimates from Decision Trees. MLCW 2005: 41-55
15		Nitesh V. Chawla, Kevin W. Bowyer: Designing Multiple Classifier Systems for Face Recognition. Multiple Classifier Systems 2005: 407-416
14		Nitesh V. Chawla: Data Mining for Imbalanced Datasets: An Overview. The Data Mining and Knowledge Discovery Handbook 2005: 853-867
13		Nitesh V. Chawla, Grigoris J. Karakoulas: Learning From Labeled And Unlabeled Data: An Empirical Study Across Techniques And Domains. J. Artif. Intell. Res. (JAIR) 23: 331-366 (2005)
	2004
12		Predrag Radivojac, Nitesh V. Chawla, A. Keith Dunker, Zoran Obradovic: Classification and knowledge discovery in protein databases. Journal of Biomedical Informatics 37(4): 224-239 (2004)
11		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)
10		Nitesh V. Chawla, Nathalie Japkowicz, Aleksander Kotcz: Editorial: special issue on learning from imbalanced data sets. SIGKDD Explorations 6(1): 1-6 (2004)
	2003
9		Nitesh V. Chawla, Aleksandar Lazarevic, Lawrence O. Hall, Kevin W. Bowyer: SMOTEBoost: Improving Prediction of the Minority Class in Boosting. PKDD 2003: 107-119
8		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)
	2002
7		Steven Eschrich, Nitesh V. Chawla, Lawrence O. Hall: Generalization Methods in Bioinformatics. BIOKDD 2002: 25-32
6		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
5		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)
	2001
4		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
3		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
2		Nitesh V. Chawla, Steven Eschrich, Lawrence O. Hall: Creating Ensembles of Classifiers. ICDM 2001: 580-581
	1999
1		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

Coauthor Index

1	Albert-László Barabási	[25] [38]
2	Nicholas Blumm	[38]
3	Kevin W. Bowyer	[1] [3] [4] [5] [6] [8] [9] [11] [15] [17] [28]
4	Randal C. Burns	[19] [27]
5	Michael J. Chapple	[23]
6	Amitabh Chaudhary	[20]
7	Nicholas Christakis	[38]
8	David A. Cieslak	[22] [26] [29] [31] [32] [33] [35] [36] [37] [39]
9	Darcy A. Davis	[38]
10	A. Keith Dunker	[12]
11	Steven Eschrich	[2] [7]
12	Mohamed Medhat Gaber	[30] [42]
13	João Gama (Joao Gama)	[30] [42]
14	Auroop R. Ganguly	[30] [41] [42]
15	Marta Gonzalez	[25]
16	David Hachen	[25]
17	Lawrence O. Hall	[1] [2] [3] [4] [5] [6] [7] [8] [9] [11] [31]
18	Mary P. Harper	[18]
19	Nathalie Japkowicz	[10]
20	Ajay Joshi	[31]
21	Grigoris J. Karakoulas	[13]
22	W. Philip Kegelmeyer	[1] [3] [4] [5] [6] [8] [11]
23	Aleksander Kotcz	[10]
24	Brett Lantz	[25]
25	Aleksandar Lazarevic	[9]
26	Qi Liao	[29]
27	Ryan Lichtenwalter	[33]
28	Yang Liu	[18]
29	Gregory R. Madey	[25]
30	Tanu Malik	[19] [27]
31	Sean McRoskey	[40]
32	Thomas E. Moore	[3] [4] [6] [8]
33	Christopher Moretti	[34]
34	James Notwell	[40]
35	Zoran Obradovic	[12]
36	Olufemi A. Omitaomu	[30] [42]
37	Alec Pawling	[20] [25]
38	Christian Poellabauer	[40]
39	Predrag Radivojac	[12]
40	Timothy W. Schoenharl	[25]
41	Elizabeth Shriberg	[18]
42	Clayton Springer	[3] [4] [8]
43	Karsten Steinhaeuser	[34] [41]
44	Andreas Stolcke	[18]
45	Aaron Striegel	[23] [29]
46	Jared Sylvester	[21] [24]
47	Gábor Szabó	[25]
48	Alexander S. Szalay	[19]
49	Douglas Thain	[22] [33] [34] [36]
50	Ranga Raju Vatsavai	[30] [42]
51	Pu Wang	[25]
52	Ping Yan	[25]

Colors in the list of coauthors