The application of an oblique-projected Landweber method to a model of supervised learning

DOI10.1016/j.mcm.2005.12.010zbMath1130.94014OpenAlexW2101730908MaRDI QIDQ2473156

Yanyan Li

Publication date: 26 February 2008

Published in: Mathematical and Computer Modelling (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.mcm.2005.12.010

zbMATH Keywords

supervised learningpreconditionerchannel representationnonnegative constraintprojected Landweber

Mathematics Subject Classification ID

Numerical optimization and variational techniques (65K10) Machine vision and scene understanding (68T45) Channel models (including quantum) in information and communication theory (94A40)

Related Items (5)

Proximal Splitting Methods in Signal Processing ⋮ Convergence results for stochastic convex feasibility problem using random Mann and simultaneous projection iterative algorithms in Hilbert space ⋮ Weak, strong and linear convergence of the CQ-method via the regularity of Landweber operators ⋮ Complexity reduction for sign configurations through the KP II equation and its information-theoretic aspects ⋮ On the proximal Landweber Newton method for a class of nonsmooth convex problems

Cites Work

• Projection methods for variational inequalities with application to the traffic assignment problem
• Iteration methods for convexly constrained ill-posed problems in hilbert space
• Numerical Optimization
• Projected Landweber method and preconditioning
• Fuzzy systems as universal approximators
• Error Bound and Reduced-Gradient Projection Algorithms for Convex Minimization over a Polyhedral Set
• Interior Methods for Nonlinear Optimization
• Enumeration of Seven-Argument Threshold Functions
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