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Publications
| Karsten Steinhaeuser, Nitesh V. Chawla, Auroop R. Ganguly (2009).
"An Exploration of Climate Data Using Complex Networks."
ACM SIGKDD Workshop on Knowledge Discovery from Sensor Data (SensorKDD). |
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| Jim Notwell, Sean McRoskey, Nitesh V. Chawla, Christian Poellabauer(2009).
"Mining in Mobile Environment."
ACM SIGKDD Workshop on Knowledge Discovery from Sensor Data (SensorKDD). |
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| Troy Raeder, Nitesh V. Chawla (2009). "Model Monitor (M^2): Evaluating, Comparing, and Monitoring Models." Journal of Machine Learning Research (JMLR). |
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| Troy Raeder, Nitesh V. Chawla (July 2009). "Modeling a Store's Product Space as a Social Network." ACM/IEEE Conference on Advances in Social Network Analysis and Mining (ASONAM). |
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| Ryan N. Lichtenwalter and Nitesh V. Chawla (April 2009).
"Adaptive Methods for
Classification in Arbitrarily Imbalanced and Drifting Data Streams.
Pacific-Asia Conference on Knowledge Discovery and Data
Mining Workshop for Data Mining When Classes are Imbalanced and Errors
Have Costs (ICEC)., pg. 86-97.
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| David A. Cieslak and Nitesh V. Chawla (2009). "A Framework for Monitoring Classifiers' Performance: When and Why Failure Occurs?" Knowledge and Information Systems (KAIS), 18(1), pg. 83-108.
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| David A. Cieslak, Nitesh V. Chawla (December 2008). "Start Globally, Optimize Locally, Predict Globally: Improving Performance on Unbalanced Data." IEEE International Conference on Data Mining (ICDM), pg. 143-152. |
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| Christopher Moretti, Karsten Steinhaeuser, Douglas Thain, Nitesh V. Chawla (December 2008). "Scaling Up Classifiers to Cloud Computers." IEEE International Conference on Data Mining (ICDM), pg. 472-481. |
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| Darcy Davis, Nitesh V. Chawla, Nicholas Blumm,
Nicholas Christakis, Albert-Laszlo Barabasi
(October 2008). "Predicting individual disease risk based on medical
history" ACM Conference on Information and
Knowledge Management (CIKM), pg. 769-778. | pdf | |
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| David A. Cieslak, Nitesh V. Chawla, and Douglas Thain (October 2008). "Troubleshooting Thousands of Jobs on Production Grids Using Data Mining Techniques" IEEE/ACM International Conference on Grid Computing (GRID), pg. 217-224.
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| David A. Cieslak and Nitesh V. Chawla (September 2008). "Learning Decision Trees for Unbalanced Data" European Conference on Machine Learning (ECML), pg. 241-256.
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| Qi Liao, David A. Cieslak, Aaron D. Striegel, and Nitesh V. Chawla (June 2008).
"Using selective, short-term memory to improve resilience against DDoS exhaustion attacks."
Security and Communication Networks, 1(4), pg. 287-299.
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| David A. Cieslak and Nitesh V. Chawla (May 2008). "Analyzing Classifier Performance on Imbalanced Datasets when Training and Testing Distributions Differ" Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), pg. 519-526.
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| Karsten Steinhaeuser and Nitesh V. Chawla (2008). "Is Modularity the Answer to Evaluating Community Structure in Networks?" International Workshop and Conference on Network Science (NetSci).
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| Karsten Steinhaeuser and Nitesh V. Chawla (2008). Scalable Learning with Thread-Level Parallelism." Midwest Artificial Intelligence and Cognitive Science Conference (MAICS).
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| Karsten Steinhaeuser and Nitesh V. Chawla (2008). "Community Detection in a Large Real-World Social Network." Social Computing, Behavioral Modeling and Prediction, H. Liu, J.J. Salerno, M.J. Young (Eds.), Springer Verlag.
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| Nitesh V. Chawla, David A. Cieslak, Larry Hall, and Ajay Joshi (2008). "Automatically Countering Imbalance and Its Empirical Relationship to Cost" Data Mining and Knowledge Discovery (DMKD), 17(2), pg. 225-252.
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| David A. Cieslak and Nitesh V. Chawla (October 2007). "Detecting Fracture Points in Classifier Performance." 7th IEEE International Conference on Data Mining (ICDM), pg. 123-132.
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| Vince Thomas, Nitesh V. Chawla, Kevin Bowyer, and Pat Flynn (September 2007). "Learning to Predict Gender from Iris Images." 1st IEEE Conference on Biometrics: Theory, Applications and Systems (BTAS), pg. 1-5.
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| Nitesh V. Chawla and Kevin Bowyer (July 2007). "Actively Exploring Creation of Face Spaces for Improved Face Recognition." 22nd National Conference on Artificial Intelligence (AAAI), pg. 809-814.
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| Michael J. Chapple, Nitesh V. Chawla, and Aaron Striegel (June 2007).
"Authentication anomaly detection: a case study on a virtual private network."
MineNet 2007, pg. 17-22.
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| Gregory R. Madey, Albert-Laszlo Barabasi, Nitesh V. Chawla, Marta Gonzalez, David Hachen, Brett Lantz, Alec Pawling, Timothy W. Schoenharl, Gabor Szabo, Pu Wang, and Ping Yan (May 2007). "Enhanced Situational Awareness: Application of DDDAS Concepts to Emergency and Disaster Management."
International Conference on Computational Science (ICCS), pg. 1090 - 1097.
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| Nitesh V. Chawla and Jared Sylvester (May 2007). "Exploiting Diversity in Ensembles: Improving Performance on Unbalanced Datasets."
7th International Workshop on Multiple Classifier Systems (MCS), pg. 397-406.
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| Karsten Steinhaeuser, Nitesh V. Chawla and Peter Kogge (2006). "Exploiting Thread-level Parallelism to Build Decision Trees."Workshop on Parallel and Distributed Data Mining (ECML/PKDD).
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| Nitesh V. Chawla and Xiangning Li (2006). "Pricing Scheme for Benefit Scoring."2nd Workshop on Utility Based Data Mining (UBDM/KDD).
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| Nitesh V. Chawla and David A. Cieslak (July 2006). "Evaluating Calibration of Probability Estimation Trees."AAAI Workshop on the Evaluation Methods in Machine Learnin Workshop on Utility Based Data Mining (AAAI), pg. 18-23.
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| Karsten Steinhaeuser, Nitesh V. Chawla, and Christian Poellabauer (2006).
"Towards Learning-based Sensor Management."First Workshop on Tackling Computer Systems Problems with Machine Learning Techniques (SYSML).
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| David A. Cieslak, Douglas Thain and Nitesh V. Chawla (June 2006).
"Troubleshooting Distributed Systems via Data Mining."15th IEEE International Symposium on High Performance Distributed Computing (HPDC-15), pg. 309-312.
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| Jared Sylvester and Nitesh V. Chawla (July 2006).
"Evolutionary Ensemble Creation and Thinning."IEEE International Joint Conference on Neural Networks (IJCNN), pg. 5148-5155.
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| David A. Cieslak, Nitesh V. Chawla and Aaron Striegel (May 2006).
"Combating Imbalance in Network Intrusion Data."IEEE International Conference on Granular Computing (GrC), pg. 732-737.
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