On spectral windows in supervised learning from data
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Publication:1675817
DOI10.1016/j.ipl.2010.08.011zbMath1379.68270OpenAlexW2082096076MaRDI QIDQ1675817
Giorgio Gnecco, Marcello Sanguineti
Publication date: 3 November 2017
Published in: Information Processing Letters (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.ipl.2010.08.011
regularizationanalysis of algorithmslearning from datasuboptimal solutionsprobabilistic estimatesempirical error functionals
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Cites Work
- Learning with generalization capability by kernel methods of bounded complexity
- Accuracy of suboptimal solutions to kernel principal component analysis
- Error bounds for suboptimal solutions to kernel principal component analysis
- The Hoffman-Wielandt inequality in infinite dimensions
- Random matrix approximation of spectra of integral operators
- The weight-decay technique in learning from data: an optimization point of view
- On the mathematical foundations of learning
- Approximate Minimization of the Regularized Expected Error over Kernel Models
- An Approach to Time Series Analysis
- DISCRETIZATION ERROR ANALYSIS FOR TIKHONOV REGULARIZATION
- Spectral Algorithms for Supervised Learning
- On the Eigenspectrum of the Gram Matrix and the Generalization Error of Kernel-PCA
- Regularization Techniques and Suboptimal Solutions to Optimization Problems in Learning from Data
- Theory of Reproducing Kernels
- Training neural networks with noisy data as an ill-posed problem
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