Larry J. Eshelman

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Code Compaction Using Genetic Algorithms

Paul F. Hoogendijk, Keith E. Mathias, Larry J. Eshelman, 2000, GECCO.

MOLE: A Knowledge Acquisition Tool that Buries Certainty Factors

Larry J. Eshelman, L. Eshelman, 1988, Int. J. Man Mach. Stud..

Crossover's Niche

Larry J. Eshelman, J. David Schaffer, J. D. Schaffer, 1993, ICGA.

The Effects of Control Parameters and Restarts on Search Stagnation in Evolutionary Programming

Keith E. Mathias, Larry J. Eshelman, J. David Schaffer, 1998, PPSN.

Automatic system for monitoring by independent persons who occasionally need help

Larry J. Eshelman, Srinivas Gutta, John Milanski, 2002 .

Spurious Correlations and Premature Convergence in Genetic Algorithms

Larry J. Eshelman, J. David Schaffer, J. D. Schaffer, 1990, FOGA.

Convergence Controlled Variation

Keith E. Mathias, Larry J. Eshelman, J. David Schaffer, 1996, FOGA.

Preventing Premature Convergence in Genetic Algorithms by Preventing Incest

Larry J. Eshelman, J. David Schaffer, J. D. Schaffer, 1991, ICGA.

Biases in the Crossover Landscape

Larry J. Eshelman, J. David Schaffer, Rich Caruana, 1989, ICGA.

Automatic system for monitoring by independent persons who need occasional help

Larry J. Eshelman, Srinivas Gutta, John Milanski, 2002 .

On Crossover as an Evolutionarily Viable Strategy

Larry J. Eshelman, J. David Schaffer, J. D. Schaffer, 1991, ICGA.

Development and Evaluation of Predictive Alerts for Hemodynamic Instability in ICU Patients

Larry J. Eshelman, Mohammed Saeed, Wei Zong, 2008, AMIA.

Designing Multiplierless Digital Filters Using Genetic Algorithms

Larry J. Eshelman, J. David Schaffer, J. D. Schaffer, 1993, ICGA.

The CHC Adaptive Search Algorithm: How to Have Safe Search When Engaging in Nontraditional Genetic Recombination

Larry J. Eshelman, L. Eshelman, 1990, FOGA.

The CHC Adaptive Search Algo-rithm

Larry J. Eshelman, 1991 .

User interface for managing an external database

Larry J. Eshelman, Srinivas Gutta, Hugo J. Strubbe, 2001 .

Representation and Hidden Bias II: Eliminating Defining Length Bias in Genetic Search via Shuffle Crossover

Larry J. Eshelman, J. David Schaffer, Rich Caruana, 1989, IJCAI.

MOLE: A Knowledge Acquisition Tool that Uses its Head

Larry J. Eshelman, John P. McDermott, J. McDermott, 1986, AAAI.

A Study of Control Parameters Affecting Online Performance of Genetic Algorithms for Function Optimization

Rajarshi Das, Larry J. Eshelman, J. David Schaffer, 1989, ICGA.

A Methodology for Evaluating the Performance of Alerting and Detection Algorithms Running on Continuous Patient Data

Larry J. Eshelman, Joseph J. Frassica, M Saeed, 2017 .

Using Multiple Representations to Improve Inductive Bias: Gray and Binary Coding for Genetic Algorithms

Larry J. Eshelman, J. David Schaffer, Rich Caruana, 1989, ML.

Proceedings of the 6th International Conference on Genetic Algorithms, Pittsburgh, PA, USA, July 15-19, 1995

Larry J. Eshelman, 1995, ICGA.

Foundations of Genetic Algorithms-2

Larry J. Eshelman, J. David Schaffer, J. D. Schaffer, 1993 .

Proceedings of the 6th International Conference on Genetic Algorithms

Larry J. Eshelman, L. Eshelman, 1995 .

Acquiring and Complementing the Model for Diagnostic Tasks

Larry J. Eshelman, Yumi Iwasaki, Hervé Lambert, 1988, ECAI.

Crossover Operator Biases: Exploiting the Population Distribution

Keith E. Mathias, Larry J. Eshelman, J. David Schaffer, 1997, ICGA.

A dynamic ensemble approach to robust classification in the presence of missing data

Larry J. Eshelman, Bryan Conroy, Cristhian Potes, 2015, Machine Learning.

Productive Recombination and Propagating and Preserving Schemata

Larry J. Eshelman, J. David Schaffer, J. D. Schaffer, 1994, FOGA.

Using genetic search to exploit the emergent behavior of neural networks

Larry J. Eshelman, J. David Schaffer, J. D. Schaffer, 1990 .

Using Weighted Networks to Represent Classification Knowledge in Noisy Domains

Larry J. Eshelman, Ming Tan, 1988, ML.

Proceedings of the Sixth International Conference on Genetic Algorithms : University of Pittsburgh, July 15-19, 1995

Larry J. Eshelman, 1995 .

The Effect of Incest Prevention on Genetic Drift

Keith E. Mathias, Larry J. Eshelman, J. David Schaffer, 1998, FOGA.

Niches in NK-Landscapes

Keith E. Mathias, Larry J. Eshelman, J. David Schaffer, 2000, FOGA.

MOLE: A Tenacious Knowledge-Acquisition Tool

Larry J. Eshelman, Ming Tan, John P. McDermott, 1987, Int. J. Man Mach. Stud..

Predicting respiratory instability in the ICU

Larry J. Eshelman, Mohammed Saeed, Colleen M. Ennett, 2008, 2008 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

Hemodynamic Instability Prediction Through Continuous Multiparameter Monitoring in ICU

Hanqing Cao, Larry J. Eshelman, Mohammed Saeed, 2010 .