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» Combining Multiple Kernels by Augmenting the Kernel Matrix
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COMBINATORICS
2006
221views more  COMBINATORICS 2006»
14 years 11 months ago
Kernels of Directed Graph Laplacians
Abstract. Let G denote a directed graph with adjacency matrix Q and indegree matrix D. We consider the Kirchhoff matrix L = D - Q, sometimes referred to as the directed Laplacian. ...
John S. Caughman IV, J. J. P. Veerman
NIPS
2004
15 years 1 months ago
Dependent Gaussian Processes
Gaussian processes are usually parameterised in terms of their covariance functions. However, this makes it difficult to deal with multiple outputs, because ensuring that the cova...
Phillip Boyle, Marcus R. Frean
PKDD
2010
Springer
188views Data Mining» more  PKDD 2010»
14 years 10 months ago
Semi-supervised Abstraction-Augmented String Kernel for Multi-level Bio-Relation Extraction
ervised Abstraction-Augmented String Kernel for Multi-Level Bio-Relation Extraction Pavel Kuksa1 , Yanjun Qi2 , Bing Bai2 , Ronan Collobert2 , Jason Weston3 , Vladimir Pavlovic1 , ...
Pavel P. Kuksa, Yanjun Qi, Bing Bai, Ronan Collobe...
PKDD
2009
Springer
138views Data Mining» more  PKDD 2009»
15 years 6 months ago
Margin and Radius Based Multiple Kernel Learning
A serious drawback of kernel methods, and Support Vector Machines (SVM) in particular, is the difficulty in choosing a suitable kernel function for a given dataset. One of the appr...
Huyen Do, Alexandros Kalousis, Adam Woznica, Melan...
ICML
2008
IEEE
16 years 16 days ago
Composite kernel learning
The Support Vector Machine (SVM) is an acknowledged powerful tool for building classifiers, but it lacks flexibility, in the sense that the kernel is chosen prior to learning. Mul...
Marie Szafranski, Yves Grandvalet, Alain Rakotomam...