Convergence of the IRWLS Procedure to the Support Vector Machine Solution

DOI10.1162/0899766052530875zbMath1092.68649OpenAlexW2141915722WikidataQ47388070 ScholiaQ47388070MaRDI QIDQ5696477

Carlos Bousoño-Calzón, Fernando Pérez-Cruz, Antonio Artés-Rodríguez

Publication date: 18 October 2005

Published in: Neural Computation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1162/0899766052530875

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Least squares and related methods for stochastic control systems (93E24)

Related Items (5)

Iteratively reweighted least square for asymmetric L₂-Loss support vector regression ⋮ Primal and dual model representations in kernel-based learning ⋮ Regularized least squares support vector regression for the simultaneous learning of a function and its derivatives ⋮ An algebraic characterization of the optimum of regularized kernel methods ⋮ Blind equalization using the IRWLS formulation of the support vector machine

Cites Work

• Benchmarking least squares support vector machine classifiers
• SVC-based equalizer for burst TDMA transmissions.

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