Bayesian network based extreme learning machine for subjectivity detection

DOI10.1016/J.JFRANKLIN.2017.06.007zbMath1395.68271OpenAlexW2734205292WikidataQ57727502 ScholiaQ57727502MaRDI QIDQ1661455

Paolo Gastaldo, Edoardo Ragusa, Iti Chaturvedi, Erik Cambria, Rodolfo Zunino

Publication date: 16 August 2018

Published in: Journal of the Franklin Institute (Search for Journal in Brave)

Full work available at URL: http://hdl.handle.net/10220/44342

Mathematics Subject Classification ID

Monte Carlo methods (65C05) Learning and adaptive systems in artificial intelligence (68T05) Applications of Markov chains and discrete-time Markov processes on general state spaces (social mobility, learning theory, industrial processes, etc.) (60J20) Natural language processing (68T50)

Related Items (5)

Asynchronous boundary stabilization for T-S fuzzy Markov jump delay reaction-diffusion neural networks ⋮ The dual PC algorithm and the role of Gaussianity for structure learning of Bayesian networks ⋮ Numerical solution and bifurcation analysis of nonlinear partial differential equations with extreme learning machines ⋮ Non-iterative and fast deep learning: multilayer extreme learning machines ⋮ Robust extreme learning machine for modeling with unknown noise

Uses Software

• SenticNet

Cites Work

• Bayesian information criteria and smoothing parameter selection in radial basis function networks
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