D-Index & Metrics Best Publications

D-Index & Metrics D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines.

Discipline name D-index D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines. Citations Publications World Ranking National Ranking
Computer Science D-index 41 Citations 8,034 301 World Ranking 5476 National Ranking 2678

Overview

What is he best known for?

The fields of study Amaury Lendasse is best known for:

  • Statistics
  • Machine learning
  • Bankruptcy prediction

Algorithm is intertwined with Projection (relational algebra) and Computation in his research. His Quantum mechanics study frequently involves adjacent topics like Nonlinear system, Gaussian and Term (time). His study ties his expertise on Quantum mechanics together with the subject of Nonlinear system. His Programming language study frequently involves adjacent topics like Toolbox and Set (abstract data type). His research is interdisciplinary, bridging the disciplines of Programming language and Set (abstract data type). He links adjacent fields of study such as Series (stratigraphy) and Context (archaeology) in the subject of Paleontology. Much of his study explores Context (archaeology) relationship to Paleontology. His Artificial intelligence study frequently draws connections to other fields, such as Image (mathematics). Many of his studies on Image (mathematics) apply to Artificial intelligence as well.

His most cited work include:

  • OP-ELM: Optimally Pruned Extreme Learning Machine (662 citations)
  • Methodology for long-term prediction of time series (310 citations)
  • High-Performance Extreme Learning Machines: A Complete Toolbox for Big Data Applications (204 citations)

What are the main themes of his work throughout his whole career to date

Artificial intelligence is closely attributed to Pattern recognition (psychology) in his study. He combines Machine learning and Time series in his research. In his papers, he integrates diverse fields, such as Artificial neural network and Extreme learning machine. In his research, he performs multidisciplinary study on Algorithm and Data mining. In his study, Amaury Lendasse carries out multidisciplinary Data mining and Artificial neural network research. His research is interdisciplinary, bridging the disciplines of Regression and Statistics. His research on Regression often connects related topics like Statistics. His studies link Nonlinear system with Quantum mechanics. His study in Quantum mechanics extends to Nonlinear system with its themes.

Amaury Lendasse most often published in these fields:

  • Artificial intelligence (92.38%)
  • Machine learning (66.67%)
  • Artificial neural network (51.43%)

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Best Publications

OP-ELM: Optimally Pruned Extreme Learning Machine

Yoan Miche;A. Sorjamaa;P. Bas;O. Simula.
IEEE Transactions on Neural Networks (2010)

848 Citations

Extreme Learning Machine

Erik Cambria;Guang-Bin Huang;Liyanaarachchi Lekamalage Chamara Kasun;Hongming Zhou.
(2013)

617 Citations

Methodology for long-term prediction of time series

Antti Sorjamaa;Jin Hao;Nima Reyhani;Yongnan Ji.
Neurocomputing (2007)

440 Citations

High-Performance Extreme Learning Machines: A Complete Toolbox for Big Data Applications

Anton Akusok;Kaj-Mikael Bjork;Yoan Miche;Amaury Lendasse.
IEEE Access (2015)

265 Citations

Mutual information for the selection of relevant variables in spectrometric nonlinear modelling

Fabrice Rossi;Amaury Lendasse;Damien François;Vincent Wertz.
Chemometrics and Intelligent Laboratory Systems (2006)

264 Citations

TROP-ELM: A double-regularized ELM using LARS and Tikhonov regularization

Yoan Miche;Mark van Heeswijk;Patrick Bas;Olli Simula.
Neurocomputing (2011)

244 Citations

Nonlinear projection with curvilinear distances: Isomap versus curvilinear distance analysis

John Aldo Lee;Amaury Lendasse;Michel Verleysen.
Neurocomputing (2004)

218 Citations

GPU-accelerated and parallelized ELM ensembles for large-scale regression

Mark van Heeswijk;Yoan Miche;Erkki Oja;Amaury Lendasse.
Neurocomputing (2011)

179 Citations

Non-linear financial time series forecasting application to the Bel 20 stock market index

Amaury Lendasse;Eric de Bodt;Vincent Wertz;Michel Verleysen.
European Journal of Economic and Social Systems (2000)

177 Citations

A robust nonlinear projection method

John Aldo Lee;Amaury Lendasse;Nicolas Donckers;Michel Verleysen.
the european symposium on artificial neural networks (2000)

167 Citations

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