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GECCO
2006
Springer
162views Optimization» more  GECCO 2006»
15 years 4 months ago
Evolutionary learning with kernels: a generic solution for large margin problems
In this paper we embed evolutionary computation into statistical learning theory. First, we outline the connection between large margin optimization and statistical learning and s...
Ingo Mierswa
VLDB
2000
ACM
120views Database» more  VLDB 2000»
15 years 4 months ago
Integrating the UB-Tree into a Database System Kernel
Multidimensional access methods have shown high potential for significant performance improvements in various application domains. However, only few approaches have made their way...
Frank Ramsak, Volker Markl, Robert Fenk, Martin Zi...
118
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AAAI
2006
15 years 2 months ago
The Robot Intelligence Kernel
The Robot Intelligence Kernel (RIK) is a portable, reconfigurable suite of perceptual, behavioral, and cognitive capabilities that can be used across many different platforms, env...
David J. Bruemmer, Douglas A. Few, Miles C. Walton...
PAMI
2010
168views more  PAMI 2010»
14 years 11 months ago
Surface-from-Gradients without Discrete Integrability Enforcement: A Gaussian Kernel Approach
—Representative surface reconstruction algorithms taking a gradient field as input enforces the integrability constraint in a discrete manner. While enforcing integrability allo...
Heung-Sun Ng, Tai-Pang Wu, Chi-Keung Tang
AIA
2007
15 years 2 months ago
Improving the aggregating algorithm for regression
Kernel Ridge Regression (KRR) and the recently developed Kernel Aggregating Algorithm for Regression (KAAR) are regression methods based on Least Squares. KAAR has theoretical adv...
Steven Busuttil, Yuri Kalnishkan, Alexander Gammer...