A Self-Organizing Flock of Condors
By A. R. Butt, Rongmei Zhang, Y. Charlie Hu, W. Lafayette. International Conference on Software Composition, 2003
363 citations recorded by the source corpus.
Subfields: Computer Networks and Communications, Information Systems
View Paper: https://www.semanticscholar.org/paper/ba139970536410d997aeaa7e1380ae97875a5a59
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Computer Networks and Communications
In Information Systems
Citations in the corpus
- Error Minimized Extreme Learning Machine With Growth of Hidden Nodes and Incremental Learning (2009, background): “Computational hidden nodes adopted in such SLFNs include additive/RBF hidden nodes, multiplicative nodes, fuzzy rules [11], fully complex nodes [12], [ 13 ], hinging functions [14], high-order nodes [15], ridge polynomials [16], wavelets [17], [18], Fourier series [19], etc.”
- Extreme learning machines: a survey (2011, background): “In high speed digital communication systems, equalizers are very often used at receivers to recover the original symbols from the received signals [34, 52].”
- Enhanced random search based incremental extreme learning machine (2008, background): “The hidden nodes of SLFNs can be neuron alike or non-neuron alike, including additive or radial basis function (RBF) type of nodes [8], multiplicative nodes, fuzzy rules [10], fully complex nodes [15, 19 ], hinging functions [2], high-order nodes [5], ridge polynomials [22], wavelets [3,4], Fourier ”
- Extreme Learning Machine for Regression and Multiclass Classification (2012, methodology): “The original solutions (21) of ELM [12], [13], [26], TERELM [22], and the weighted regularized ELM [21] are not able to apply kernels in their implementations.”