J. David Schaffer

	2011
32		Ravi Mathur, J. David Schaffer, Walker H. Land Jr., John J. Heine, Jonathan M. Hernandez, Timothy Yeatman: Perturbation and candidate analysis to combat overfitting of gene expression microarray data. I. J. Computational Biology and Drug Design 4(4): 307-315 (2011)
31		Ravi Mathur, J. David Schaffer, Walker H. Land Jr., John J. Heine, Steven Eschrich, Timothy Yeatman: Evolutionary computation with noise perturbation and cluster analysis to discover biomarker sets. Procedia CS 6: 153-158 (2011)
30		R. Batllori, Craig B. Laramee, Walker H. Land Jr., J. David Schaffer: Evolving spiking neural networks for robot control. Procedia CS 6: 329-334 (2011)
	2010
29		Heike Sichtig, J. David Schaffer, Alberto Riva: Evolving Spiking Neural Networks for predicting transcription factor binding sites. IJCNN 2010: 1-8
	2009
28		J. David Schaffer, Heike Sichtig, Craig B. Laramee: A series of failed and partially successful fitness functions for evolving spiking neural networks. GECCO (Companion) 2009: 2661-2664
	2008
27		Heike Sichtig, J. David Schaffer, Craig B. Laramee: SSNNS -: a suite of tools to explore spiking neural networks. GECCO (Companion) 2008: 1787-1790
	2003
26		Lalitha Agnihotri, Nevenka Dimitrova, Thomas McGee, Sylvie Jeannin, J. David Schaffer, Jan Nesvadba: Envolvable Visual Commercial Detector. CVPR (2) 2003: 79-84
	2002
25		J. David Schaffer, Lalitha Agnihotri, Nevenka Dimitrova, Thomas McGee, Sylvie Jeannin: Improving Digital Video Commercial Detectors With Genetic Algorithms. GECCO 2002: 1212-1218
	2000
24		Srinivas Gutta, Kaushal Kurapati, K. P. Lee, Jacquelyn Martino, John Milanski, J. David Schaffer, John Zimmerman: TV Content Recommender System. AAAI/IAAI 2000: 1121-1122
23		Keith E. Mathias, Larry J. Eshelman, J. David Schaffer: Niches in NK-Landscapes. FOGA 2000: 27-46
22		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
	1998
21		J. David Schaffer, Murali Mani, Larry J. Eshelman, Keith E. Mathias: The Effect of Incest Prevention on Genetic Drift. FOGA 1998: 235-244
20		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
19		Larry J. Eshelman, Keith E. Mathias, J. David Schaffer: Crossover Operator Biases: Exploiting the Population Distribution. ICGA 1997: 354-361
	1996
18		Larry J. Eshelman, Keith E. Mathias, J. David Schaffer: Convergence Controlled Variation. FOGA 1996: 203-224
	1994
17		Larry J. Eshelman, J. David Schaffer: Productive Recombination and Propagating and Preserving Schemata. FOGA 1994: 299-313
	1993
16		J. David Schaffer, Larry J. Eshelman: Designing Multiplierless Digital Filters Using Genetic Algorithms. ICGA 1993: 439-444
15		Larry J. Eshelman, J. David Schaffer: Crossover's Niche. ICGA 1993: 9-14
	1992
14		Larry J. Eshelman, J. David Schaffer: Real-Coded Genetic Algorithms and Interval-Schemata. FOGA 1992: 187-202
	1991
13		Larry J. Eshelman, J. David Schaffer: Preventing Premature Convergence in Genetic Algorithms by Preventing Incest. ICGA 1991: 115-122
12		J. David Schaffer, Larry J. Eshelman: On Crossover as an Evolutionarily Viable Strategy. ICGA 1991: 61-68
	1990
11		J. David Schaffer, Larry J. Eshelman, Daniel Offutt: Spurious Correlations and Premature Convergence in Genetic Algorithms. FOGA 1990: 102-112
	1989
10		J. David Schaffer: Proceedings of the 3rd International Conference on Genetic Algorithms, George Mason University, Fairfax, Virginia, USA, June 1989 Morgan Kaufmann 1989
9		Larry J. Eshelman, Rich Caruana, J. David Schaffer: Biases in the Crossover Landscape. ICGA 1989: 10-19
8		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
7		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
6		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
	1988
5		Rich Caruana, J. David Schaffer: Representation and Hidden Bias: Gray vs. Binary Coding for Genetic Algorithms. ML 1988: 153-161
	1987
4		J. David Schaffer, Amy Morishima: An Adaptive Crossover Distribution Mechanism for Genetic Algorithms. ICGA 1987: 36-40
	1985
3		J. David Schaffer: Learning Multiclass Pattern Discrimination. ICGA 1985: 74-79
2		J. David Schaffer: Multiple Objective Optimization with Vector Evaluated Genetic Algorithms. ICGA 1985: 93-100
1		J. David Schaffer, John J. Grefenstette: Multi-Objective Learning via Genetic Algorithms. IJCAI 1985: 593-595

Coauthor Index

1	Lalitha Agnihotri	[25] [26]
2	Lex Augusteijn	[22]
3	R. Batllori	[30]
4	Rich Caruana	[5] [6] [7] [8] [9]
5	Rajarshi Das	[8]
6	Nevenka Dimitrova	[25] [26]
7	Steven Eschrich	[31]
8	Larry J. Eshelman	[6] [7] [8] [9] [11] [12] [13] [14] [15] [16] [17] [18] [19] [20] [21] [22] [23]
9	John J. Grefenstette	[1]
10	Srinivas Gutta	[24]
11	John J. Heine	[31] [32]
12	Jonathan M. Hernandez	[32]
13	Paul F. Hoogendijk	[22]
14	Sylvie Jeannin	[25] [26]
15	Kaushal Kurapati	[24]
16	Walker H. Land Jr.	[30] [31] [32]
17	Craig B. Laramee	[27] [28] [30]
18	K. P. Lee	[24]
19	Murali Mani	[20] [21]
20	Jacquelyn Martino	[24]
21	Keith E. Mathias	[18] [19] [20] [21] [22] [23]
22	Ravi Mathur	[31] [32]
23	Thomas McGee	[25] [26]
24	John Milanski	[24]
25	Amy Morishima	[4]
26	Jan Nesvadba	[26]
27	Daniel Offutt	[11]
28	Alberto Riva	[29]
29	Heike Sichtig	[27] [28] [29]
30	Rik van de Wiel	[22]
31	Timothy Yeatman	[31] [32]
32	John Zimmerman	[24]

Colors in the list of coauthors

Last update Fri May 25 01:42:58 2012 CET by the DBLP Team — Data released under the ODC-BY 1.0 license — See also our legal information page