J. David Schaffer

47 papers A* 2A 10B 2Journal 7Unranked 25

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	On the Preservation of Input/Output Directed Graph Informativeness Under Crossover. Complex. Andreas Duus Pape, J. David Schaffer, Hiroki Sayama, Christoper Zosh
2024	J	`jnl`	On the Preservation of Input/Output Directed Graph Informativeness under Crossover. CoRR Andreas Duus Pape, J. David Schaffer, Hiroki Sayama, Christopher Zosh
2023	B	`conf`	A Bio-Inspired Computational Astrocyte Model for Spiking Neural Networks. IJCNN Jacob Kiggins, J. David Schaffer, Cory E. Merkel
2021	J	`jnl`	Towards an Automatic Speech-Based Diagnostic Test for Alzheimer's Disease. Frontiers Comput. Sci. Roozbeh Sadeghian, J. David Schaffer, Stephen A. Zahorian
2020	—	`conf`	Evolving Spiking Neural Networks for Robot Sensory-motor Decision Tasks of Varying Difficulty. NICE J. David Schaffer
2017	A	`conf`	Speech Processing Approach for Diagnosing Dementia in an Early Stage. INTERSPEECH Roozbeh Sadeghian, J. David Schaffer, Stephen A. Zahorian
2016	J	`jnl`	A novel approach to signal classification with an application to identifying the alcoholic brain. Appl. Soft Comput. Arnab Roy, J. David Schaffer, Craig B. Laramee
2015	—	`conf`	Evolving spiking neural networks: A novel growth algorithm corrects the teacher. CISDA J. David Schaffer
2015	—	`conf`	Predicting with Confidence: Extensions to the GRNN Oracle Enabling Quantification of Confidence in Predictions. Complex Adaptive Systems Walker H. Land Jr., J. David Schaffer
2014	J	`jnl`	New crossover operators for multiple subset selection tasks. CoRR Arnab Roy, J. David Schaffer, Craig B. Laramee
2013	—	`conf`	Evolving Spike Neural Network Sensors to Characterize the Alcoholic Brain Using Visually Evoked Response Potential. Complex Adaptive Systems Arnab Roy, J. David Schaffer, Craig B. Laramee
2013	—	`conf`	Investigating the GRNN Oracle as a Method for Combining Multiple Predictive Models of Colon Cancer Recurrence from Gene Microarrays. Complex Adaptive Systems Aaron S. Campbell, Walker H. Land Jr., Dan Margolis, Ravi Mathur, J. David Schaffer
2012	—	`conf`	Evolving data sets to highlight the performance differences between machine learning classifiers. GECCO (Companion) Thomas Raway, J. David Schaffer, Kenneth J. Kurtz, Hiroki Sayama
2012	—	`conf`	GRNN Ensemble Classifier for Lung Cancer Prognosis Using Only Demographic and TNM features. Complex Adaptive Systems J. David Schaffer, Jin-Woo Park, Erin Barnes, Qiyi Lu, Xingye Qiao, Youping Deng, Yan Li, Walker H. Land Jr.
2011	—	`conf`	Evolutionary computation with noise perturbation and cluster analysis to discover biomarker sets. Complex Adaptive Systems Ravi Mathur, J. David Schaffer, Walker H. Land Jr., John J. Heine, Steven Eschrich, Timothy Yeatman
2011	—	`conf`	Evolving spiking neural networks for robot control. Complex Adaptive Systems R. Batllori, Craig B. Laramee, Walker H. Land Jr., J. David Schaffer
2011	J	`jnl`	Perturbation and candidate analysis to combat overfitting of gene expression microarray data. Int. J. Comput. Biol. Drug Des. Ravi Mathur, J. David Schaffer, Walker H. Land Jr., John J. Heine, Jonathan M. Hernandez, Timothy Yeatman
2010	B	`conf`	Evolving Spiking Neural Networks for predicting transcription factor binding sites. IJCNN Heike Sichtig, J. David Schaffer, Alberto Riva
2009	—	`conf`	A series of failed and partially successful fitness functions for evolving spiking neural networks. GECCO (Companion) J. David Schaffer, Heike Sichtig, Craig B. Laramee
2008	—	`conf`	SSNNS -: a suite of tools to explore spiking neural networks. GECCO (Companion) Heike Sichtig, J. David Schaffer, Craig B. Laramee
2003	—	`conf`	Envolvable Visual Commercial Detector. CVPR (2) Lalitha Agnihotri, Nevenka Dimitrova, Thomas McGee, Sylvie Jeannin, J. David Schaffer, Jan Nesvadba
2002	A	`conf`	Improving Digital Video Commercial Detectors With Genetic Algorithms. GECCO J. David Schaffer, Lalitha Agnihotri, Nevenka Dimitrova, Thomas McGee, Sylvie Jeannin
2000	A	`conf`	Code Compaction Using Genetic Algorithms. GECCO Keith E. Mathias, Larry J. Eshelman, J. David Schaffer, Lex Augusteijn, Paul F. Hoogendijk, Rik van de Wiel
2000	A	`conf`	Niches in NK-Landscapes. FOGA Keith E. Mathias, Larry J. Eshelman, J. David Schaffer
2000	—	`conf`	TV Content Recommender System. AAAI/IAAI Srinivas Gutta, Kaushal Kurapati, K. P. Lee, Jacquelyn Martino, John Milanski, J. David Schaffer, John Zimmerman
1998	A	`conf`	The Effect of Incest Prevention on Genetic Drift. FOGA J. David Schaffer, Murali Mani, Larry J. Eshelman, Keith E. Mathias
1998	A	`conf`	The Effects of Control Parameters and Restarts on Search Stagnation in Evolutionary Programming. PPSN Keith E. Mathias, J. David Schaffer, Larry J. Eshelman, Murali Mani
1997	—	`conf`	Crossover Operator Biases: Exploiting the Population Distribution. ICGA Larry J. Eshelman, Keith E. Mathias, J. David Schaffer
1996	A	`conf`	Convergence Controlled Variation. FOGA Larry J. Eshelman, Keith E. Mathias, J. David Schaffer
1994	A	`conf`	Productive Recombination and Propagating and Preserving Schemata. FOGA Larry J. Eshelman, J. David Schaffer
1993	—	`conf`	Crossover's Niche. ICGA Larry J. Eshelman, J. David Schaffer
1993	—	`conf`	Designing Multiplierless Digital Filters Using Genetic Algorithms. ICGA J. David Schaffer, Larry J. Eshelman
1992	A	`conf`	Real-Coded Genetic Algorithms and Interval-Schemata. FOGA Larry J. Eshelman, J. David Schaffer
1991	—	`conf`	On Crossover as an Evolutionarily Viable Strategy. ICGA J. David Schaffer, Larry J. Eshelman
1991	—	`conf`	Preventing Premature Convergence in Genetic Algorithms by Preventing Incest. ICGA Larry J. Eshelman, J. David Schaffer
1990	A	`conf`	Spurious Correlations and Premature Convergence in Genetic Algorithms. FOGA J. David Schaffer, Larry J. Eshelman, Daniel Offutt
1989	—	`conf`	A Study of Control Parameters Affecting Online Performance of Genetic Algorithms for Function Optimization. ICGA J. David Schaffer, Rich Caruana, Larry J. Eshelman, Rajarshi Das
1989	—	`conf`	Biases in the Crossover Landscape. ICGA Larry J. Eshelman, Rich Caruana, J. David Schaffer
1989	—	`ed.`	Proceedings of the 3rd International Conference on Genetic Algorithms, George Mason University, Fairfax, Virginia, USA, June 1989 ICGA J. David Schaffer
1989	A*	`conf`	Representation and Hidden Bias II: Eliminating Defining Length Bias in Genetic Search via Shuffle Crossover. IJCAI Rich Caruana, Larry J. Eshelman, J. David Schaffer
1989	—	`conf`	Using Multiple Representations to Improve Inductive Bias: Gray and Binary Coding for Genetic Algorithms. ML Rich Caruana, J. David Schaffer, Larry J. Eshelman
1988	J	`jnl`	Adaptive knowledge representation: A content sensitive recombination mechanism for genetic algorithms. Int. J. Intell. Syst. J. David Schaffer, Amy Morishima
1988	—	`conf`	Representation and Hidden Bias: Gray vs. Binary Coding for Genetic Algorithms. ML Rich Caruana, J. David Schaffer
1987	—	`conf`	An Adaptive Crossover Distribution Mechanism for Genetic Algorithms. ICGA J. David Schaffer, Amy Morishima
1985	—	`conf`	Learning Multiclass Pattern Discrimination. ICGA J. David Schaffer
1985	A*	`conf`	Multi-Objective Learning via Genetic Algorithms. IJCAI J. David Schaffer, John J. Grefenstette
1985	—	`conf`	Multiple Objective Optimization with Vector Evaluated Genetic Algorithms. ICGA J. David Schaffer