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» A Boosting Algorithm for Regression
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141
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ESANN
2008
15 years 4 months ago
Selection of important input variables for RBF network using partial derivatives
In regression problems, making accurate predictions is often the primary goal. Also, relevance of inputs in the prediction of an output would be valuable information in many cases....
Jarkko Tikka, Jaakko Hollmén
FSMNLP
2008
Springer
15 years 4 months ago
Learning with Weighted Transducers
Weighted finite-state transducers have been used successfully in a variety of natural language processing applications, including speech recognition, speech synthesis, and machine ...
Corinna Cortes, Mehryar Mohri
131
Voted
NIPS
2007
15 years 4 months ago
Random Features for Large-Scale Kernel Machines
To accelerate the training of kernel machines, we propose to map the input data to a randomized low-dimensional feature space and then apply existing fast linear methods. The feat...
Ali Rahimi, Benjamin Recht
131
Voted
NIPS
2007
15 years 4 months ago
Using Deep Belief Nets to Learn Covariance Kernels for Gaussian Processes
We show how to use unlabeled data and a deep belief net (DBN) to learn a good covariance kernel for a Gaussian process. We first learn a deep generative model of the unlabeled da...
Ruslan Salakhutdinov, Geoffrey E. Hinton
107
Voted
FLAIRS
2001
15 years 4 months ago
Hybrid Decision Tree Learners with Alternative Leaf Classifiers: An Empirical Study
Therehasbeensurprisinglylittle researchso far that systematicallyinvestigatedthe possibilityof constructinghybrid learningalgorithmsbysimplelocal modificationsto decision tree lea...
Alexander K. Seewald, Johann Petrak, Gerhard Widme...