Martin Michalowski, Ph.D.

Affiliations: 
2008 Computer Science University of Southern California, Los Angeles, CA, United States 
Area:
Computer Science
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"Martin Michalowski"

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Craig A. Knoblock grad student 2008 USC
 (A general approach to using problem instance data for model refinement in constraint satisfaction problems.)
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Bouchard B, Bouchard K, Brown N, et al. (2018) Reports of the Workshops of the 32nd AAAI Conference on Artificial Intelligence Ai Magazine. 39: 45-56
Wilk S, Michalowski M, Michalowski W, et al. (2016) Comprehensive Mitigation Framework for Concurrent Application of Multiple Clinical Practice Guidelines. Journal of Biomedical Informatics
Agrawal V, Archibald C, Bhatt M, et al. (2013) The AAAI-13 Conference Workshops Ai Magazine. 34: 108
Michalowski M, Knoblock CA, Bayer K, et al. (2007) Exploiting automatically inferred constraint-models for building identification in satellite imagery Gis: Proceedings of the Acm International Symposium On Advances in Geographic Information Systems. 35-42
Michalowski M, Knoblock CA, Choueiry BY. (2007) Reformulating constraint models using input data Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 4612: 402-404
Bayer KM, Michalowski M, Choueiry BY, et al. (2007) Reformulating constraint satisfaction problems to improve scalability Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 4612: 64-79
Bayer KM, Michalowski M, Choueiry BY, et al. (2007) Reformulating CSPs for scalability with application to geospatial reasoning Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 4741: 164-179
Michalowski M, Knoblock CA. (2006) A generalized query framework for geospatial reasoning Proceedings of the National Conference On Artificial Intelligence. 2: 1922-1923
Michalowski M, Thakkar S, Knoblock CA. (2005) Automatically utilizing secondary sources to align information across sources Ai Magazine. 26: 33-44
Minton SN, Nanjo C, Knoblock CA, et al. (2005) A heterogeneous field matching method for record linkage Proceedings - Ieee International Conference On Data Mining, Icdm. 314-321
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