716 search results - page 55 / 144 » Optimizing Sorting with Machine Learning Algorithms |
102
Voted
ICML
2007
IEEE
16 years 3 months ago
2007
IEEE
In the paper we propose a new type of regularization procedure for training sparse Bayesian methods for classification. Transforming Hessian matrix of log-likelihood function to d...
108
Voted
ICML
2006
IEEE
16 years 3 months ago
2006
IEEE
Semi-Supervised Support Vector Machines (S3 VMs) are an appealing method for using unlabeled data in classification: their objective function favors decision boundaries which do n...
116
click to vote
GECCO
2008
Springer
15 years 3 months ago
2008
Springer
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...
105
Voted
ICML
2004
IEEE
16 years 3 months ago
2004
IEEE
Surrogate maximization (or minimization) (SM) algorithms are a family of algorithms that can be regarded as a generalization of expectation-maximization (EM) algorithms. There are...
ICML
2001
IEEE
16 years 3 months ago
2001
IEEE
This is a survey of some theoretical results on boosting obtained from an analogous treatment of some regression and classi cation boosting algorithms. Some related papers include...