Bounds on the complexity of neural‐network models and comparison with linear methods
From MaRDI portal
Publication:4707174
DOI10.1002/ACS.746zbMATH Open1029.93002OpenAlexW2116625308MaRDI QIDQ4707174
Kateřina Hlaváčková-Schindler, Marcello Sanguineti
Publication date: 10 June 2003
Published in: International Journal of Adaptive Control and Signal Processing (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1002/acs.746
neural networksnonlinear modelslinear modelscurse of dimensionalitynonlinear approximation theorypolynomially bounded complexity
Related Items (6)
Comparison of four gradient-learning algorithms for neural network Wiener models ⋮ Linear neural networks revisited: from PageRank to family happiness ⋮ Title not available (Why is that?) ⋮ Title not available (Why is that?) ⋮ A Framework for the Construction of Upper Bounds on the Number of Affine Linear Regions of ReLU Feed-Forward Neural Networks ⋮ Title not available (Why is that?)
This page was built for publication: Bounds on the complexity of neural‐network models and comparison with linear methods
Report a bug (only for logged in users!)Click here to report a bug for this page (MaRDI item Q4707174)