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» Ensemble Methods in Machine Learning
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119
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ICMLA
2010
14 years 10 months ago
Classification Models with Global Constraints for Ordinal Data
Ordinal classification is a form of multi-class classification where there is an inherent ordering between the classes, but not a meaningful numeric difference between them. Althou...
Jaime S. Cardoso, Ricardo Sousa
119
Voted
PRL
2011
14 years 7 months ago
Efficient approximate Regularized Least Squares by Toeplitz matrix
Machine Learning based on the Regularized Least Square (RLS) model requires one to solve a system of linear equations. Direct-solution methods exhibit predictable complexity and s...
Sergio Decherchi, Paolo Gastaldo, Rodolfo Zunino
101
Voted
ICML
2009
IEEE
16 years 1 months ago
Learning with structured sparsity
This paper investigates a new learning formulation called structured sparsity, which is a naturalextensionofthestandardsparsityconceptinstatisticallearningandcompressivesensing. B...
Junzhou Huang, Tong Zhang, Dimitris N. Metaxas
ICML
2007
IEEE
16 years 1 months ago
Learning state-action basis functions for hierarchical MDPs
This paper introduces a new approach to actionvalue function approximation by learning basis functions from a spectral decomposition of the state-action manifold. This paper exten...
Sarah Osentoski, Sridhar Mahadevan
104
Voted
ICML
2007
IEEE
16 years 1 months ago
Adaptive mesh compression in 3D computer graphics using multiscale manifold learning
This paper investigates compression of 3D objects in computer graphics using manifold learning. Spectral compression uses the eigenvectors of the graph Laplacian of an object'...
Sridhar Mahadevan