Can Dictionary-based Computational Models Outperform the Best Linear Ones?

0360287 - ÚI 2012 RIV GB eng J - Journal Article
Gnecco, G. - Kůrková, Věra - Sanguineti, M.
Can Dictionary-based Computational Models Outperform the Best Linear Ones?
Neural Networks. Roč. 24, č. 8 (2011), s. 881-887. ISSN 0893-6080. E-ISSN 1879-2782
R&D Projects: GA MŠMT OC10047
Grant - others:CNR - AV ČR project 2010-2012(XE) Complexity of Neural-Network and Kernel Computational Models
Institutional research plan: CEZ:AV0Z10300504
Keywords : dictionary-based approximation * linear approximation * rates of approximation * worst-case error * Kolmogorov width * perceptron networks
Subject RIV: IN - Informatics, Computer Science
Impact factor: 2.182, year: 2011

Cited: 2

--- ANDRAS, P. Function Approximation Using Combined Unsupervised and Supervised Learning. IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS. ISSN 2162-237X, MAR 2014, vol. 25, no. 3, p. 495-505. [WOS]
--- CARNEIRO, H.C.C. - FRANCA, F.M.G. - LIMA, P.M.V. Multilingual part-of-speech tagging with weightless neural networks. NEURAL NETWORKS. ISSN 0893-6080, JUN 2015, vol. 66, p. 11-21. [WOS]

Permanent Link: http://hdl.handle.net/11104/0197874