Robust learning of large-scale fuzzy cognitive maps via the lasso from noisy time series

Volume: 113, Pages: 23 - 38
Published: Dec 1, 2016
Abstract
Fuzzy cognitive maps (FCMs) have been used to describe and model the behavior of complex systems. Learning large-scale FCMs from a small amount of data without any a priori knowledge remains an outstanding problem. In particular, a significant challenge arises when limited amounts of data are accompanied by noise. Here, we develop a framework based on the least absolute shrinkage and selection operator (lasso), a convex optimization method, to...
Paper Details
Title
Robust learning of large-scale fuzzy cognitive maps via the lasso from noisy time series
Published Date
Dec 1, 2016
Volume
113
Pages
23 - 38
Citation AnalysisPro
  • Scinapse’s Top 10 Citation Journals & Affiliations graph reveals the quality and authenticity of citations received by a paper.
  • Discover whether citations have been inflated due to self-citations, or if citations include institutional bias.