2008 |
26 | EE | Heike Sichtig,
J. David Schaffer,
Craig B. Laramee:
SSNNS -: a suite of tools to explore spiking neural networks.
GECCO (Companion) 2008: 1787-1790 |
2003 |
25 | EE | Lalitha Agnihotri,
Nevenka Dimitrova,
Thomas McGee,
Sylvie Jeannin,
J. David Schaffer,
Jan Nesvadba:
Envolvable Visual Commercial Detector.
CVPR (2) 2003: 79-84 |
2002 |
24 | | J. David Schaffer,
Lalitha Agnihotri,
Nevenka Dimitrova,
Thomas McGee,
Sylvie Jeannin:
Improving Digital Video Commercial Detectors With Genetic Algorithms.
GECCO 2002: 1212-1218 |
2000 |
23 | | 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 |
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 | EE | 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 |