1062 search results - page 125 / 213 » Sublinear Optimization for Machine Learning |
115
Voted
NIPS
2007
15 years 3 months ago
2007
We present a general boosting method extending functional gradient boosting to optimize complex loss functions that are encountered in many machine learning problems. Our approach...
134
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ICML
2002
IEEE
16 years 3 months ago
2002
IEEE
Kernel-based learning algorithms work by embedding the data into a Euclidean space, and then searching for linear relations among the embedded data points. The embedding is perfor...
123
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EUROCAST
2007
Springer
15 years 8 months ago
2007
Springer
Abstract a paradigm of modern Machine Learning (ML) which uses rewards and punishments to guide the learning process. One of the central ideas of RL is learning by “direct-online...
132
Voted
ICML
2009
IEEE
16 years 3 months ago
2009
IEEE
We present a generalized version of spectral clustering using the graph p-Laplacian, a nonlinear generalization of the standard graph Laplacian. We show that the second eigenvecto...
126
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ICML
2007
IEEE
16 years 3 months ago
2007
IEEE
We propose a method for the classification of matrices. We use a linear classifier with a novel regularization scheme based on the spectral 1-norm of its coefficient matrix. The s...