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Larry J. Eshelman
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2010 – 2019
- 2016
- [j3]Bryan Conroy, Larry J. Eshelman, Cristhian Potes, Minnan Xu-Wilson:
A dynamic ensemble approach to robust classification in the presence of missing data. Mach. Learn. 102(3): 443-463 (2016)
2000 – 2009
- 2008
- [c22]Larry J. Eshelman, K. P. Lee, Joseph J. Frassica, Wei Zong, Larry Nielsen, Mohammed Saeed:
Development and Evaluation of Predictive Alerts for Hemodynamic Instability in ICU Patients. AMIA 2008 - 2000
- [c21]Keith E. Mathias, Larry J. Eshelman, J. David Schaffer:
Niches in NK-Landscapes. FOGA 2000: 27-46 - [c20]Keith E. Mathias, Larry J. Eshelman, J. David Schaffer, Lex Augusteijn, Paul F. Hoogendijk, Rik van de Wiel:
Code Compaction Using Genetic Algorithms. GECCO 2000: 710-717
1990 – 1999
- 1998
- [c19]J. David Schaffer, Murali Mani, Larry J. Eshelman, Keith E. Mathias:
The Effect of Incest Prevention on Genetic Drift. FOGA 1998: 235-244 - [c18]Keith E. Mathias, J. David Schaffer, Larry J. Eshelman, Murali Mani:
The Effects of Control Parameters and Restarts on Search Stagnation in Evolutionary Programming. PPSN 1998: 398-407 - 1997
- [c17]Larry J. Eshelman, Keith E. Mathias, J. David Schaffer:
Crossover Operator Biases: Exploiting the Population Distribution. ICGA 1997: 354-361 - 1996
- [c16]Larry J. Eshelman, Keith E. Mathias, J. David Schaffer:
Convergence Controlled Variation. FOGA 1996: 203-224 - 1995
- [e1]Larry J. Eshelman:
Proceedings of the 6th International Conference on Genetic Algorithms, Pittsburgh, PA, USA, July 15-19, 1995. Morgan Kaufmann 1995, ISBN 1-55860-370-0 [contents] - 1994
- [c15]Larry J. Eshelman, J. David Schaffer:
Productive Recombination and Propagating and Preserving Schemata. FOGA 1994: 299-313 - 1993
- [c14]Larry J. Eshelman, J. David Schaffer:
Crossover's Niche. ICGA 1993: 9-14 - [c13]J. David Schaffer, Larry J. Eshelman:
Designing Multiplierless Digital Filters Using Genetic Algorithms. ICGA 1993: 439-444 - 1992
- [c12]Larry J. Eshelman, J. David Schaffer:
Real-Coded Genetic Algorithms and Interval-Schemata. FOGA 1992: 187-202 - 1991
- [c11]J. David Schaffer, Larry J. Eshelman:
On Crossover as an Evolutionarily Viable Strategy. ICGA 1991: 61-68 - [c10]Larry J. Eshelman, J. David Schaffer:
Preventing Premature Convergence in Genetic Algorithms by Preventing Incest. ICGA 1991: 115-122 - 1990
- [c9]J. David Schaffer, Larry J. Eshelman, Daniel Offutt:
Spurious Correlations and Premature Convergence in Genetic Algorithms. FOGA 1990: 102-112 - [c8]Larry J. Eshelman:
The CHC Adaptive Search Algorithm: How to Have Safe Search When Engaging in Nontraditional Genetic Recombination. FOGA 1990: 265-283
1980 – 1989
- 1989
- [c7]Larry J. Eshelman, Rich Caruana, J. David Schaffer:
Biases in the Crossover Landscape. ICGA 1989: 10-19 - [c6]J. David Schaffer, Rich Caruana, Larry J. Eshelman, Rajarshi Das:
A Study of Control Parameters Affecting Online Performance of Genetic Algorithms for Function Optimization. ICGA 1989: 51-60 - [c5]Rich Caruana, J. David Schaffer, Larry J. Eshelman:
Using Multiple Representations to Improve Inductive Bias: Gray and Binary Coding for Genetic Algorithms. ML 1989: 375-378 - [c4]Rich Caruana, Larry J. Eshelman, J. David Schaffer:
Representation and Hidden Bias II: Eliminating Defining Length Bias in Genetic Search via Shuffle Crossover. IJCAI 1989: 750-755 - 1988
- [j2]Larry J. Eshelman:
MOLE: A Knowledge Acquisition Tool that Buries Certainty Factors. Int. J. Man Mach. Stud. 29(5): 563-577 (1988) - [c3]Hervé Lambert, Larry J. Eshelman, Yumi Iwasaki:
Acquiring and Complementing the Model for Diagnostic Tasks. ECAI 1988: 73-78 - [c2]Ming Tan, Larry J. Eshelman:
Using Weighted Networks to Represent Classification Knowledge in Noisy Domains. ML 1988: 121-134 - 1987
- [j1]Larry J. Eshelman, Damien Ehret, John P. McDermott, Ming Tan:
MOLE: A Tenacious Knowledge-Acquisition Tool. Int. J. Man Mach. Stud. 26(1): 41-54 (1987) - 1986
- [c1]Larry J. Eshelman, John P. McDermott:
MOLE: A Knowledge Acquisition Tool that Uses its Head. AAAI 1986: 950-955
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