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ICML
2004
IEEE
15 years 12 months ago
Gradient LASSO for feature selection
LASSO (Least Absolute Shrinkage and Selection Operator) is a useful tool to achieve the shrinkage and variable selection simultaneously. Since LASSO uses the L1 penalty, the optim...
Yongdai Kim, Jinseog Kim
ATS
2003
IEEE
105views Hardware» more  ATS 2003»
15 years 11 months ago
Minimizing Defective Part Level Using a Linear Programming-Based Optimal Test Selection Method
Recent probabilistic test generation approaches have proven that detecting single stuck-at faults multiple times is effective at reducing the defective part level (DPL). Unfortuna...
Yuxin Tian, Michael R. Grimaila, Weiping Shi, M. R...
EPIA
2003
Springer
15 years 11 months ago
Automatic Selection of Table Areas in Documents for Information Extraction
: information contained in companies’ financial statements is valuable for decision making at various levels. Much of the relevant information in such documents is contained in t...
Ana Costa e Silva, Alípio Jorge, Luí...
DAGM
2006
Springer
15 years 10 months ago
Model Selection in Kernel Methods Based on a Spectral Analysis of Label Information
Abstract. We propose a novel method for addressing the model selection problem in the context of kernel methods. In contrast to existing methods which rely on hold-out testing or t...
Mikio L. Braun, Tilman Lange, Joachim M. Buhmann
DAGM
2006
Springer
15 years 10 months ago
Parameterless Isomap with Adaptive Neighborhood Selection
Abstract. Isomap is a highly popular manifold learning and dimensionality reduction technique that effectively performs multidimensional scaling on estimates of geodesic distances....
Nathan Mekuz, John K. Tsotsos