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Minimization of Empirical Error over Perceptron Networks
Supervised learning by perceptron networks is investigated as an approximate minimization of empirical error functional.
BA - Obecná matematika
- 2005 •
- D
Rok uplatnění
D - Stať ve sborníku
Learning from Data as an Optimization and Inverse Problem
Learning form data is investigated as minimization of empirical error functional in spaces of continuous functions and spaces defined by kernels. Using methods from theory of inverse problems, an alternative proof of Repres...
IN - Informatika
- 2012 •
- D •
- Link
Rok uplatnění
D - Stať ve sborníku
Výsledek na webu
Learning from Data as an Inverse Problem
We reformulate the problem of minimization of an empirical error functional as a linear inverse problem by introducing an operator defined in terms of evaluations at the input data....
BA - Obecná matematika
- 2004 •
- D
Rok uplatnění
D - Stať ve sborníku
Learning with Generalization Capability by Kernel Methods of Bounded Complexity
Learning from data with generalization capability is studied in the framework of minimization of regularized empirical error functionals over nested families of hypothesis sets with increasing model complexity....
BA - Obecná matematika
- 2005 •
- Jx
Rok uplatnění
Jx - Nezařazeno - Článek v odborném periodiku (Jimp, Jsc a Jost)
Learning from Data by Neural Networks of Limited Complexity.
Learning from data formalized as a minimization of a relularized empirical error is studied in terms of approximate minimization over sets of functions computable by networks with increasing number of hidden units....
BA - Obecná matematika
- 2003 •
- D
Rok uplatnění
D - Stať ve sborníku
Neural Networks Learning as Approximate Optimization.
Learning from data will be studied in the framework of approximate minimization of regularized empirical error functionals. There will be derived estimates of speed of convergence of infima achievable over approximations of...
BA - Obecná matematika
- 2003 •
- D
Rok uplatnění
D - Stať ve sborníku
Approximate Minimization of the Regularized Expected Error over Kernel Models
Learning from data under constraints on model complexity is studied in terms of rates of approximate minimization of the regularized expected error functional defining the expected error. As a special case, estimates of rat...
BA - Obecná matematika
- 2008 •
- Jx
Rok uplatnění
Jx - Nezařazeno - Článek v odborném periodiku (Jimp, Jsc a Jost)
High-field side error field effects on H-mode plasma performance and their correction in ITER-like experiments on COMPASS
corresponds to the minimization of the coupling of the error field to the core plasma.The effect of high field side error fields on H-mode plasmas of different beta as obesrved experimentally is presented. Furthermore the ...
Fluids and plasma physics (including surface physics)
- 2018 •
- D
Rok uplatnění
D - Stať ve sborníku
Inverse Problems in Learning from Data
It is shown that application of methods from theory of inverse problems to learning from data leads to simple proofs of characterization of minima of empirical and expected error functionals and their regularized versions. The refor...
IN - Informatika
- 2010 •
- D
Rok uplatnění
D - Stať ve sborníku
Existence and Uniqueness of Minimization Problems with Fourier Based Stabilizers
We study minimization of regularized empirical error functional with a Fourier-based stabilizer. We prove existence and uniqueness of the solution. We also describe the shape of the minimizing function and show tha...
BA - Obecná matematika
- 2004 •
- D
Rok uplatnění
D - Stať ve sborníku
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