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Keywords
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Statistical Learning Theory
Related Publications
(704)
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Statistical Learning Theory
Statistical Learning Theory,Vladimir Vapnik
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Statistical Learning Theory
(
Citations: 9935
)
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Vladimir Vapnik
Published in 1998.
Cumulative
Annual
Citation Context
(6254)
...For a general introduction to SVM theory we cite, for example, [4, 19,
20
]...
...The basic training principle of SVM, motivated by statistical learning theory [
20
], is that the expected classification error for unseen test samples is minimized, so that SVM defines a good predictive model...
A. Cassioli
,
et al.
Machine learning for global optimization
...The support vector machine (SVM) is a wellknown statistical learning method for data mining [
54
]...
Jing Hu
,
et al.
On linear programs with linear complementarity constraints
...The approach is based on statistical learning, which can cope well with noisy signals and can generalize to unknown inputs (Vapnik
1998
)...
Aaron S. W. Wong
,
et al.
Visual gaze analysis of robotic pedestrians moving in urban space
...One of such justiflcations is addressed concisely by (
Vapnik, 1998
) that \one should solve the problem (classiflcation) directly and never solve a more general problem (modeling p(yjx)) as an intermediate step."...
ShuangHong Yang
,
et al.
Discriminative Feature Selection by Nonparametric Bayes Error Minimiza...
...Quantile regression (whether linear or nonlinear) falls into this category, as do modern classification techniques such as the support vector machine (
Vapnik, 1998
) and the psilearner (Shen et al., 2003)...
...Interestingly, this ℓ2adjusted absolute deviation loss is the same as the socalled “ǫinsensitive linear loss” for support vector regression (
Vapnik, 1998
) with ǫ = 1/λ...
...For modeling and prediction of the binary responses, we mainly consider marginbased procedures such as logistic regression, support vector machines (
Vapnik, 1998
), and boosting (Freund and Schapire, 1997)...
Yoonkyung Lee
,
et al.
Regularization of CaseSpecific Parameters for Robustness and Efficien...
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Citations
(9935)
Machine learning for global optimization
(
Citations: 3
)
A. Cassioli
,
D. Di Lorenzo
,
M. Locatelli
,
F. Schoen
,
M. Sciandrone
Journal:
Computational Optimization and Applications  COMPUT OPTIM APPL
, vol. 45, no. 1, pp. 125, 2012
On linear programs with linear complementarity constraints
(
Citations: 4
)
Jing Hu
,
John E. Mitchell
,
JongShi Pang
,
Bin Yu
Journal:
Journal of Global Optimization
, pp. 123, 2012
Regularized Posteriors in Linear IllPosed Inverse Problems
(
Citations: 4
)
JEANPIERRE FLORENS
,
ANNA SIMONI
Published in 2012.
Visual gaze analysis of robotic pedestrians moving in urban space
(
Citations: 1
)
Aaron S. W. Wong
,
Stephan K. Chalup
,
Shashank Bhatia
,
Arash Jalalian
,
Jason Kulk
,
Steven Nicklin
,
Michael J. Ostwald
Journal:
Architectural Science Review
, vol. aheadofp, no. aheadofp, pp. 111, 2012
Discriminative Feature Selection by Nonparametric Bayes Error Minimization
(
Citations: 1
)
ShuangHong Yang
,
BaoGang Hu
Journal:
IEEE Transactions on Knowledge and Data Engineering  TKDE
, vol. 24, no. 8, pp. 14221434, 2012