468 search results - page 16 / 94 » Optimization of in-network data reduction |
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SAC
2006
ACM
15 years 3 months ago
2006
ACM
“The curse of dimensionality” is pertinent to many learning algorithms, and it denotes the drastic raise of computational complexity and classification error in high dimension...
GECCO
2003
Springer
15 years 2 months ago
2003
Springer
Abstract. Feature extraction based on evolutionary search offers new possibilities for improving classification accuracy and reducing measurement complexity in many data mining and...
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ICCV
2009
IEEE
16 years 2 months ago
2009
IEEE
We present a manifold learning approach to dimensionality
reduction that explicitly models the manifold as a mapping
from low to high dimensional space. The manifold is
represen...
IEEEMM
2007
14 years 9 months ago
2007
— Microarray technology offers a high throughput means to study expression networks and gene regulatory networks in cells. The intrinsic nature of high dimensionality and small s...
CDC
2009
IEEE
14 years 7 months ago
2009
IEEE
Abstract-- Local convergence is a limitation of many optimization approaches for multimodal functions. For hybrid model learning, this can mean a compromise in accuracy. We develop...