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127
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JASIS
2000
143views more  JASIS 2000»
15 years 2 months ago
Discovering knowledge from noisy databases using genetic programming
s In data mining, we emphasize the need for learning from huge, incomplete and imperfect data sets (Fayyad et al. 1996, Frawley et al. 1991, Piatetsky-Shapiro and Frawley, 1991). T...
Man Leung Wong, Kwong-Sak Leung, Jack C. Y. Cheng
SC
1995
ACM
15 years 6 months ago
Input/Output Characteristics of Scalable Parallel Applications
Rapid increases in computing and communication performance are exacerbating the long-standing problem of performance-limited input/output. Indeed, for many otherwise scalable para...
Phyllis Crandall, Ruth A. Aydt, Andrew A. Chien, D...
NIPS
1997
15 years 4 months ago
Learning Generative Models with the Up-Propagation Algorithm
Up-propagation is an algorithm for inverting and learning neural network generative models. Sensory input is processed by inverting a model that generates patterns from hidden var...
Jong-Hoon Oh, H. Sebastian Seung
116
Voted
EVOW
2009
Springer
15 years 9 months ago
Evolving Simple Art-Based Games
Evolutionary art has a long and distinguished history, and genetic programming is one of only a handful of AI techniques which is used in graphic design and the visual arts. A rece...
Simon Colton, Cameron Browne
118
Voted
ATAL
2009
Springer
15 years 9 months ago
A self-organizing neural network architecture for intentional planning agents
This paper presents a model of neural network embodiment of intentions and planning mechanisms for autonomous agents. The model bridges the dichotomy of symbolic and non-symbolic ...
Budhitama Subagdja, Ah-Hwee Tan