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106
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GECCO
2007
Springer
198views Optimization» more  GECCO 2007»
15 years 10 months ago
On the design of optimisers for surface reconstruction
In many industrial applications the need for an efficient and high-quality reconstruction of free-form surfaces does exist. Surface Reconstruction – the generation of CAD models...
Tobias Wagner, Thomas Michelitsch, Alexei Sacharow
ICML
2003
IEEE
16 years 4 months ago
The Use of the Ambiguity Decomposition in Neural Network Ensemble Learning Methods
We analyze the formal grounding behind Negative Correlation (NC) Learning, an ensemble learning technique developed in the evolutionary computation literature. We show that by rem...
Gavin Brown, Jeremy L. Wyatt
159
Voted
ICPR
2008
IEEE
15 years 10 months ago
Multimodal biometrics management using adaptive score-level combination
This paper presents a new evolutionary approach for adaptive combination of multiple biometrics to dynamically ensure the performance for the desired level of security. The adapti...
Ajay Kumar, Vivek Kanhangad, David Zhang
CODES
1996
IEEE
15 years 8 months ago
Two-level Partitioning of Image Processing Algorithms for the Parallel Map-oriented Machine
The partitioning of image processing algorithms with a novel hardware/software co-designframework (CoDe-X) is presented in this paper, where a new Xputer-architecture (parallel Ma...
Reiner W. Hartenstein, Jürgen Becker, Rainer ...
152
Voted
IJCAI
2001
15 years 5 months ago
R-MAX - A General Polynomial Time Algorithm for Near-Optimal Reinforcement Learning
R-max is a very simple model-based reinforcement learning algorithm which can attain near-optimal average reward in polynomial time. In R-max, the agent always maintains a complet...
Ronen I. Brafman, Moshe Tennenholtz