David A. Cieslak, Ph.D.

Affiliations: 
2009 University of Notre Dame, Notre Dame, IN, United States 
Area:
Computer Science
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"David Cieslak"

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Nitesh Chawla grad student 2009 Notre Dame
 (Finding problems in, proposing solutions to, and performing analysis on imbalanced data.)
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Publications

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Regola N, Cieslak DA, Chawla NV. (2013) The need to consider hardware selection when designing big data applications supported by metadata Big Data Management, Technologies, and Applications. 381-396
Regola N, Cieslak DA, Chawla NV. (2012) The constraints of magnetic versus flash disk capabilities in big data analysis Acm International Conference Proceeding Series. 4-9
Cieslak DA, Hoens TR, Chawla NV, et al. (2012) Hellinger distance decision trees are robust and skew-insensitive Data Mining and Knowledge Discovery. 24: 136-158
Liu W, Chawla S, Cieslak DA, et al. (2010) A robust decision tree algorithm for imbalanced data sets Proceedings of the 10th Siam International Conference On Data Mining, Sdm 2010. 766-777
Cieslak DA, Chawla NV. (2009) A framework for monitoring classifiers' performance: When and why failure occurs? Knowledge and Information Systems. 18: 83-108
Chawla NV, Thain D, Lichtenwalter R, et al. (2008) Data mining on the grid for the grid Ipdps Miami 2008 - Proceedings of the 22nd Ieee International Parallel and Distributed Processing Symposium, Program and Cd-Rom
Cieslak DA, Chawla NV. (2008) Start globally, optimize locally, predict globally: Improving performance on imbalanced data Proceedings - Ieee International Conference On Data Mining, Icdm. 143-152
Cieslak DA, Chawla NV, Thain DL. (2008) Troubleshooting thousands of jobs on production grids using data mining techniques Proceedings - Ieee/Acm International Workshop On Grid Computing. 217-224
Chawla NV, Cieslak DA, Hall LO, et al. (2008) Automatically countering imbalance and its empirical relationship to cost Data Mining and Knowledge Discovery. 17: 225-252
Cieslak DA, Chawla NV. (2008) Learning decision trees for unbalanced data Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 5211: 241-256
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