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DIAL Publications

2007

  1. Alec Pawling, Nitesh V. Chawla, and Gregory Madey. “Anomaly Detection in a Mobile Communication Network.” Computational and Mathematical Organizational Theory, 13(4):407–422, 2007. PDF
  2. David A. Cieslak and Nitesh V. Chawla. “Detecting Fractures in Classifier Performance.” Proceedings of the 7th IEEE International Conference on Data Mining (ICDM), pp. 123–132, 2007. PDF
  3. Vince Thomas, Nitesh V. Chawla, Kevin W. Bowyer, and Patrick J. Flynn. “Learning to Predict Gender from Iris Images.” Proceedings of the 1st IEEE International Conference on Biometrics: Theory, Applications, and Systems (BTAS), pp. 1–5, 2007. PDF
  4. Nitesh V. Chawla and Kevin W. Bowyer. “Actively Exploring Creation of Face Space(s) for Improved Face Recognition.” Proceedings of the National Conference on Artificial Intelligence (AAAI), 22(1):809–814, 2007. PDF
  5. Michael J. Chapple, Nitesh V. Chawla, and Aaron D. Striegel. “Authentication Anomaly Detection: A Case Study on a Virtual Private Network.” Proceedings of the 3rd Annual ACM Workshop on Mining Network Data (MineNet), pp. 17–22, 2007. PDF
  6. Gregory R. Madey, Albert-László Barabási, Nitesh V. Chawla, Marta Gonzales, David Hachen, Brett Lantz, Alec Pawling, Timothy W. Schoenharl, Gábor Szabó, Pu Wang, and Ping Yan. “Enhanced Situational Awareness: Application of DDDAS Concepts to Emergency and Disaster Management.” Proceedings of the 7th International Conference on Computational Science (ICCS), pp. 1090–1097, 2007. PDF
  7. Nitesh V. Chawla and Jared Sylvester. “Exploiting Diversity in Ensembles: Improving Performance on Unbalanced Datasets.” Multiple Classifier Systems (MCS), pp. 397–406, 2007. PDFTanu Malik, Randal Burns, and Nitesh V. Chawla. “A Black-Box Approach to Query Cardinality Estimation.” ACM Conference on Innovative Data Systems Research (CIDR), pp. 56–67, 2007. PDF

2006

  1. Tanu Malik, Randal Burns, Nitesh V. Chawla, and Alexander S. Szalay. “Estimating Query Result Sizes for Proxy Caching in Scientific Database Federations.” Proceedings of the ACM/IEEE Conference on Supercomputing (SC), pp. 102–115, 2006. PDF
  2. Yang Liu, Nitesh V. Chawla, Mary P. Harper, Elizabeth Shriberg, and Andreas Stolcke. “A Study in Machine Learning from Imbalanced Data for Sentence Boundary Detection in Speech.” Journal of Computer Speech and Language, 20(4):468–494, 2006. PDF
  3. Karsten Steinhaeuser, Nitesh V. Chawla, and Peter M. Kogge. “Exploiting Thread-Level Parallelism to Build Decision Trees.” Proceedings of the ECML/PKDD International Workshop on Parallel and Distributed Data Mining, pp. 13–24, 2006. PDF
  4. Dinesh Rajan, Christian Poellabauer, and Nitesh V. Chawla. “Resource Access Pattern Mining for Dynamic Energy Management.” Proceedings of the ECML/PKDD Workshop on Automatic Computing: A New Challenge for Machine Learning, 2006. PDF
  5. Alec Pawling, Nitesh V. Chawla, and Amitabh Chaudhary. “Evaluation of Summarization Schemes for Learning in Streams.” Proceedings of the 17th European Conference on Machine Learning and the 10th European Conference on Principles and Practice of Knowledge Discovery in Databases (ECML/PKDD), pp. 347–358, 2006. PDF
  6. Nitesh V. Chawla and Xiangning Li. “Pricing Based Framework for Benefit Scoring.” Proceedings of the ACM SIGKDD 2nd International Workshop on Utility-Based Data Mining (UBDM), pp. 65–75, 2006. PDF
  7. Danny Roobaert, Grigoris Karakoulas, and Nitesh V. Chawla. ” Information Gain, Correlation and Support Vector Machines.” Feature Extraction: Foundations and Applications, pp. 463–470, 2006. PDF
  8. Jared Sylvester and Nitesh V. Chawla. “Evolutionary Ensemble Creation and Thinning.” Proceedings of the IEEE International Joint Conference on Neural Networks (IJCNN), pp. 5148–5155, 2006. PDF
  9. Nitesh V. Chawla and David A. Cieslak. “Evaluating Probability Estimates from Decision Trees.” Proceedings of the AAAI Workshop on Evaluation Methods for Machine Learning, 2006. PDF
  10. Nitesh V. Chawla. “Many Are Better Than One: Improving Probabilistic Estimates from Decision Trees.” Machine Learning Challenges, pp. 41–55, 2006. PDF
  11. Karsten Steinhaeuser, Nitesh V. Chawla, and Christian Poellabauer. “Towards Learning-Based Sensor Management.” Proceedings of the 1st Workshop on Tackling Computer Systems Problems with Machine Learning (SysML), 2006. PDF
  12. Alec Pawling, Nitesh V. Chawla, and Gregory Madey. “Anomaly Detection in a Mobile Communication Network.” Annual Conference of the North American Association for Computational Social and Organizational Science (NAACSOS), pp. 407–422, 2006. PDF
  13. David A. Cieslak, Douglas L. Thain, and Nitesh V. Chawla. “Troubleshooting Distributed Systems via Data Mining.” Proceedings of the 15th IEEE International Symposium on High Performance Distributed Computing (HPDC), pp. 309–312, 2006. PDF
  14. David A. Cieslak, Nitesh V. Chawla, and Aaron D. Striegel. “Combating Imbalance in Network Intrusion Datasets.” Proceedings of the IEEE International Conference on Granular Computing (GrC), pp. 732–737, 2006. PDF
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