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ORCIDArmand Prieditis
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Journal Articles
- 1999
[j7]Robert Davis, Armand Prieditis:
Designing Optimal Sequential Experiments for a Bayesian Classifier. IEEE Trans. Pattern Anal. Mach. Intell. 21(3): 193-201 (1999)- 1998
- [j6]Armand Prieditis:
Depth-First Branch-and-Bound vs. Depth-Bounded IDA*. Comput. Intell. 14(2): 188-206 (1998) - [j5]Armand Prieditis, Evan Fletcher:
Two-agent IDA*. J. Exp. Theor. Artif. Intell. 10(4): 451-485 (1998) - 1997
- [j4]Armand Prieditis:
Adding upper-bound pruning to IDA*. J. Exp. Theor. Artif. Intell. 9(1): 67-81 (1997) - 1995
- [j3]Armand Prieditis, Robert Davis:
Quantitatively Relating Abstractness to the Accuracy of Admissible Heuristics. Artif. Intell. 74(1): 165-175 (1995) - 1993
- [j2]Robert Davis, Armand Prieditis:
The Expected Length of a Shortest Path. Inf. Process. Lett. 46(3): 135-141 (1993) - [j1]Armand Prieditis:
Machine Discovery of Effective Admissible Heuristics. Mach. Learn. 12: 117-141 (1993)
Conference and Workshop Papers
- 2013
- [c9]Armand Prieditis, Gang Chen:
Mapping the Internet: Geolocating Routers by Using Machine Learning. COM.Geo 2013: 101-105 - [c8]Stephanie Sapp, Armand Prieditis:
Accuracy-Based Classification EM: Combining Clustering with Prediction. MLDM 2013: 458-465 - [c7]Armand Prieditis, Moontae Lee:
When Classification becomes a Problem: Using Branch-and-Bound to Improve Classification Efficiency. MLDM 2013: 466-480 - [c6]Armand Prieditis, Stephanie Sapp:
Lazy Overfitting Control. MLDM 2013: 481-491 - 1993
- [c5]Armand Prieditis, Bhaskar Janakiraman:
Generating Effective Admissible Heuristics by Abstraction and Reconstitution. AAAI 1993: 743-748 - 1991
- [c4]Armand Prieditis:
Machine Discovery of Effective Admissible Heuristics. IJCAI 1991: 720-725 - 1989
- [c3]Jack Mostow, Armand Prieditis:
Discovering Admissible Search Heuristics by Abstracting and Optimizing. ML 1989: 240-240 - [c2]Jack Mostow, Armand Prieditis:
Discovering Admissible Heuristics by Abstracting and Optimizing: A Transformational Approach. IJCAI 1989: 701-707 - 1987
- [c1]Armand Prieditis, Jack Mostow:
PROLEARN: Towards a Prolog Interpreter that Learns. AAAI 1987: 494-498
Editorship
- 1995
- [e1]Armand Prieditis, Stuart Russell:
Machine Learning, Proceedings of the Twelfth International Conference on Machine Learning, Tahoe City, California, USA, July 9-12, 1995. Morgan Kaufmann 1995, ISBN 1-55860-377-8 [contents]
Informal and Other Publications
- 2022
- [i1]Michele Bennett, Mehdi Nekouei, Armand Prieditis, Rajesh Mehta, Ewa J. Kleczyk, Karin Hayes:
Methodology to Create Analysis-Naive Holdout Records as well as Train and Test Records for Machine Learning Analyses in Healthcare. CoRR abs/2205.03987 (2022)
Coauthor Index
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