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http://papers.nips.cc/paper/1457-prior-knowledge-in-support-vector-kernels.pdf
Prior Knowledge in Support Vector Kernels 643 sample estimate of the covariance matrix of the random vector s . %t It=OLtX, s E {±1} being a random sign. Based on this observation, we call C (9) the Tangent Covariance Matrix of the data set {Xi: i = 1, . .. ,f} with respect to the transformations Lt.
https://www.researchgate.net/publication/221619575_Prior_Knowledge_in_Support_Vector_Kernels
Prior Knowledge in Support Vector Kernels. Conference Paper ... This prior knowledge relies on the fact that topical meaningful words (e.g., noun phrases and …
https://www.researchgate.net/publication/2595840_Prior_Knowledge_in_Support_Vector_Kernels
Prior knowledge in the form of multiple polyhedral sets, each be- longing to one of two categories, is introduced into a reformulation of a linear support vector machine classier.
http://alex.smola.org/papers/1998/SchSimSmoVap98.pdf
Prior Knowledge in Support Vector Kernels Bernhard Scholkopf¨ Max–Planck–Institutf¨ur biologische Kybernetik T¨ubingen,Germany Patrice Simard, Vladimir Vapnik AT&T Research 101 Crawfords Corner Rd. Holmdel, NJ, USA Alexander J. Smola GMD FIRST Rudower Chaussee 5 Berlin, Germany Abstract We explore methods for incorporatingprior knowledge ...
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.9.5442
CiteSeerX - Document Details (Isaac Councill, Lee Giles, Pradeep Teregowda): We explore methods for incorporating prior knowledge about a problem at hand in Support Vector learning machines. We show that both invariances under group transformations and prior knowledge about locality in images can be incorporated by constructing appropriate kernel functions.
https://www.hindawi.com/journals/mpe/2010/378652/
This paper presents a novel prior knowledge-based Green's kernel for support vector regression (SVR). After reviewing the correspondence between support vector kernels used in support vector machines (SVMs) and regularization operators used in regularization networks and the use of Green's function of their corresponding regularization operators to construct support vector …Cited by: 8
http://www.kernel-machines.org/publications/SchSimSmoVap98
Methods for incorporating prior knowledge in Support Vector machines are explored. It is shown that both invariances under group transformations and prior knowledge about locality in images can be incorporated by constructing appropriate kernel functions.
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.681.5166
CiteSeerX - Document Details (Isaac Councill, Lee Giles, Pradeep Teregowda): We explore methods for incorporating prior knowledge about a problem at hand in Support Vector learning machines. We show that both invari-ances under group transformations and prior knowledge about locality in images can be incorporated by constructing appropriate kernel functions. 1
https://www.sciencedirect.com/science/article/pii/S0925231207001439
For classification, support vector machines (SVMs) have recently been introduced and quickly became the state of the art. Now, the incorporation of prior knowledge into SVMs is the key element that allows to increase the performance in many applications.Cited by: 160
https://link.springer.com/article/10.1007%2Fs00500-014-1390-x
Jul 30, 2014 · In the algorithm, multiple feature spaces have been utilized to incorporate multi-kernel functions into the framework of linear programming support vector regression (LPSVR), and then the prior knowledge which may be exact or biased from a calibrated physical simulator has also been incorporated into LPSVR by modifying optimization formulations.Cited by: 5
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