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.
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.
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OP-ELM: Optimally Pruned Extreme Learning Machine
Yoan Miche;A. Sorjamaa;P. Bas;O. Simula.
IEEE Transactions on Neural Networks (2010)
Extreme Learning Machine
Erik Cambria;Guang-Bin Huang;Liyanaarachchi Lekamalage Chamara Kasun;Hongming Zhou.
Methodology for long-term prediction of time series
Antti Sorjamaa;Jin Hao;Nima Reyhani;Yongnan Ji.
High-Performance Extreme Learning Machines: A Complete Toolbox for Big Data Applications
Anton Akusok;Kaj-Mikael Bjork;Yoan Miche;Amaury Lendasse.
IEEE Access (2015)
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)
TROP-ELM: A double-regularized ELM using LARS and Tikhonov regularization
Yoan Miche;Mark van Heeswijk;Patrick Bas;Olli Simula.
Nonlinear projection with curvilinear distances: Isomap versus curvilinear distance analysis
John Aldo Lee;Amaury Lendasse;Michel Verleysen.
GPU-accelerated and parallelized ELM ensembles for large-scale regression
Mark van Heeswijk;Yoan Miche;Erkki Oja;Amaury Lendasse.
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)
A robust nonlinear projection method
John Aldo Lee;Amaury Lendasse;Nicolas Donckers;Michel Verleysen.
the european symposium on artificial neural networks (2000)
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