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» A DC-programming algorithm for kernel selection
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ICISP
2010
Springer
14 years 1 months ago
Classification of High-Resolution NMR Spectra Based on Complex Wavelet Domain Feature Selection and Kernel-Induced Random Forest
High-resolution nuclear magnetic resonance (NMR) spectra contain important biomarkers that have potentials for early diagnosis of disease and subsequent monitoring of its progressi...
Guangzhe Fan, Zhou Wang, Seoung Bum Kim, Chivalai ...
JMLR
2011
148views more  JMLR 2011»
13 years 3 months ago
Bayesian Generalized Kernel Mixed Models
We propose a fully Bayesian methodology for generalized kernel mixed models (GKMMs), which are extensions of generalized linear mixed models in the feature space induced by a repr...
Zhihua Zhang, Guang Dai, Michael I. Jordan
CVPR
2009
IEEE
15 years 3 months ago
Let the Kernel Figure it Out; Principled Learning of Pre-processing for Kernel Classifiers
Most modern computer vision systems for high-level tasks, such as image classification, object recognition and segmentation, are based on learning algorithms that are able to se...
Peter V. Gehler, Sebastian Nowozin
ECWEB
2009
Springer
204views ECommerce» more  ECWEB 2009»
14 years 3 months ago
Computational Complexity Reduction for Factorization-Based Collaborative Filtering Algorithms
Abstract. Alternating least squares (ALS) is a powerful matrix factorization (MF) algorithm for both implicit and explicit feedback based recommender systems. We show that by using...
István Pilászy, Domonkos Tikk
JMLR
2002
106views more  JMLR 2002»
13 years 8 months ago
Some Greedy Learning Algorithms for Sparse Regression and Classification with Mercer Kernels
We present some greedy learning algorithms for building sparse nonlinear regression and classification models from observational data using Mercer kernels. Our objective is to dev...
Prasanth B. Nair, Arindam Choudhury 0002, Andy J. ...