Results 231 to 240 of about 853,208 (277)
Some of the next articles are maybe not open access.
2013
The kernel method was originally invented in Aizerman et al. (Autom. Remote Control, 25, 821–837, 1964). The key idea is to project the training set in a lower-dimensional space into a high-dimensional kernel (feature) space by means of a set of nonlinear kernel functions.
Ke-Lin Du, M. N. S. Swamy
openaire +1 more source
The kernel method was originally invented in Aizerman et al. (Autom. Remote Control, 25, 821–837, 1964). The key idea is to project the training set in a lower-dimensional space into a high-dimensional kernel (feature) space by means of a set of nonlinear kernel functions.
Ke-Lin Du, M. N. S. Swamy
openaire +1 more source
IFAC Proceedings Volumes, 2003
Abstract A disadvantage of many statistical modelling techniques is that the resulting model is extremely difficult to interpret. A number of new concepts and algorithms have been introduced by researchers to address this problem. They focus primarily on determining which inputs arc relevant in predicting the output. This work describes a transparent,
openaire +1 more source
Abstract A disadvantage of many statistical modelling techniques is that the resulting model is extremely difficult to interpret. A number of new concepts and algorithms have been introduced by researchers to address this problem. They focus primarily on determining which inputs arc relevant in predicting the output. This work describes a transparent,
openaire +1 more source
Bridging deep and multiple kernel learning: A review
Information Fusion, 2021Tinghua Wang, Wenyu Hu
exaly
Kernel-based methods for hyperspectral image classification
IEEE Transactions on Geoscience and Remote Sensing, 2005Gustau Camps-Valls, Lorenzo Bruzzone
exaly