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» Sublinear Optimization for Machine Learning
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GECCO
2008
Springer
123views Optimization» more  GECCO 2008»
13 years 11 months ago
Hierarchical evolution of linear regressors
We propose an algorithm for function approximation that evolves a set of hierarchical piece-wise linear regressors. The algorithm, named HIRE-Lin, follows the iterative rule learn...
Francesc Teixidó-Navarro, Albert Orriols-Pu...
MTA
2007
113views more  MTA 2007»
13 years 9 months ago
A framework for a video analysis tool for suspicious event detection
This paper proposes a framework to aid video analysts in detecting suspicious activity within the tremendous amounts of video data that exists in today’s world of omnipresent su...
Gal Lavee, Latifur Khan, Bhavani M. Thuraisingham
ICML
2010
IEEE
13 years 8 months ago
The Margin Perceptron with Unlearning
We introduce into the classical Perceptron algorithm with margin a mechanism of unlearning which in the course of the regular update allows for a reduction of possible contributio...
Constantinos Panagiotakopoulos, Petroula Tsampouka
GECCO
2005
Springer
218views Optimization» more  GECCO 2005»
14 years 3 months ago
Particle swarm optimization for analysis of mass spectral serum profiles
Serum profiling using mass spectrometry is an emerging technology with a great potential to provide biomarkers for complex diseases such as cancer. However, protein profiles obtai...
Habtom W. Ressom, Rency S. Varghese, Daniel Saha, ...
ROCAI
2004
Springer
14 years 3 months ago
Optimizing Area Under Roc Curve with SVMs
For many years now, there is a growing interest around ROC curve for characterizing machine learning performances. This is particularly due to the fact that in real-world problems ...
Alain Rakotomamonjy