H-Index & Metrics Top Publications
Joos Vandewalle

Joos Vandewalle

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Computer Science H-index 66 Citations 37,901 405 World Ranking 1051 National Ranking 12

Research.com Recognitions

Awards & Achievements

1999 - Member of Academia Europaea

1992 - IEEE Fellow For contributions to the mathematics of nonlinear circuits and systems

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Statistics
  • Algebra

His primary areas of study are Artificial intelligence, Support vector machine, Least squares support vector machine, Algorithm and Artificial neural network. His work deals with themes such as Sampling, Machine learning and Pattern recognition, which intersect with Artificial intelligence. His research in Support vector machine tackles topics such as Feature vector which are related to areas like Kernel.

His research integrates issues of Radial basis function kernel, Mathematical optimization, Least squares and Bayesian inference in his study of Least squares support vector machine. His work carried out in the field of Least squares brings together such families of science as Quadratic programming and Applied mathematics. Joos Vandewalle interconnects Intelligent control and Control theory, Nonlinear system in the investigation of issues within Artificial neural network.

His most cited work include:

  • Least Squares Support Vector Machine Classifiers (6712 citations)
  • A Multilinear Singular Value Decomposition (3096 citations)
  • Least Squares Support Vector Machines (2730 citations)

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

Joos Vandewalle spends much of his time researching Artificial neural network, Artificial intelligence, Algorithm, Nonlinear system and Control theory. His biological study deals with issues like Theoretical computer science, which deal with fields such as Cryptography. The various areas that Joos Vandewalle examines in his Artificial intelligence study include Machine learning, Computer vision and Pattern recognition.

The study incorporates disciplines such as Matrix, Mathematical optimization and Subspace topology in addition to Algorithm. His Nonlinear system research is multidisciplinary, relying on both CHAOS and Topology. His research on Support vector machine focuses in particular on Least squares support vector machine.

He most often published in these fields:

  • Artificial neural network (19.60%)
  • Artificial intelligence (16.46%)
  • Algorithm (16.13%)

What were the highlights of his more recent work (between 2002-2018)?

  • Artificial intelligence (16.46%)
  • Algorithm (16.13%)
  • Nonlinear system (15.23%)

In recent papers he was focusing on the following fields of study:

His scientific interests lie mostly in Artificial intelligence, Algorithm, Nonlinear system, Artificial neural network and Cellular neural network. All of his Artificial intelligence and Support vector machine and Least squares support vector machine investigations are sub-components of the entire Artificial intelligence study. His Least squares support vector machine research integrates issues from Principal component regression and Least squares.

Joos Vandewalle combines subjects such as Numerical linear algebra and Topology with his study of Nonlinear system. His work in Cellular neural network covers topics such as Robustness which are related to areas like Grayscale. In Pattern recognition, Joos Vandewalle works on issues like Kernel, which are connected to Mathematical optimization.

Between 2002 and 2018, his most popular works were:

  • Benchmarking Least Squares Support Vector Machine Classifiers (618 citations)
  • True random bit generation from a double-scroll attractor (240 citations)
  • Coupled Simulated Annealing (236 citations)

In his most recent research, the most cited papers focused on:

  • Artificial intelligence
  • Statistics
  • Algebra

His primary areas of study are Artificial intelligence, Least squares support vector machine, Algorithm, Pattern recognition and Nonlinear system. Joos Vandewalle studies Support vector machine which is a part of Artificial intelligence. His work in Support vector machine addresses subjects such as Feature vector, which are connected to disciplines such as Kernel.

Joos Vandewalle has researched Least squares support vector machine in several fields, including Principal component regression and Total least squares, Least squares. His Algorithm research includes themes of Iterative reconstruction and Aliasing. His Nonlinear system research incorporates themes from Artificial neural network, Differential, Representation and Chaotic oscillators.

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.

Top Publications

Least Squares Support Vector Machine Classifiers

J. A. K. Suykens;J. Vandewalle.
Neural Processing Letters (1999)

10988 Citations

Least Squares Support Vector Machines

Johan A K Suykens;Tony Van Gestel;Jos De Brabanter;Bart De Moor.
(2002)

5605 Citations

A Multilinear Singular Value Decomposition

Lieven De Lathauwer;Bart De Moor;Joos Vandewalle.
SIAM Journal on Matrix Analysis and Applications (2000)

4083 Citations

The Total Least Squares Problem: Computational Aspects and Analysis

Sabine Van Huffel;Joos Vandewalle.
(1987)

2097 Citations

On the Best Rank-1 and Rank-( R 1 , R 2 ,. . ., R N ) Approximation of Higher-Order Tensors

Lieven De Lathauwer;Bart De Moor;Joos Vandewalle.
SIAM Journal on Matrix Analysis and Applications (2000)

1667 Citations

Weighted least squares support vector machines: robustness and sparse approximation

J.A.K. Suykens;J. De Brabanter;L. Lukas;J. Vandewalle.
Neurocomputing (2002)

1607 Citations

Benchmarking Least Squares Support Vector Machine Classifiers

Tony Van Gestel;Johan A. K. Suykens;Bart Baesens;Stijn Viaene.
Machine Learning (2004)

844 Citations

Prognostic importance of degree of differentiation and cyst rupture in stage I invasive epithelial ovarian carcinoma

Ignace Vergote;Jos De Brabanter;Anthony Fyles;Kamma Bertelsen.
The Lancet (2001)

724 Citations

Financial time series prediction using least squares support vector machines within the evidence framework

T. Van Gestel;J.A.K. Suykens;D.-E. Baestaens;A. Lambrechts.
IEEE Transactions on Neural Networks (2001)

702 Citations

Optimal control by least squares support vector machines

J. A. K. Suykens;J. Vandewalle;B. De Moor.
Neural Networks (2001)

696 Citations

Profile was last updated on December 6th, 2021.
Research.com Ranking is based on data retrieved from the Microsoft Academic Graph (MAG).
The ranking h-index is inferred from publications deemed to belong to the considered discipline.

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Top Scientists Citing Joos Vandewalle

Johan A. K. Suykens

Johan A. K. Suykens

KU Leuven

Publications: 278

Sabine Van Huffel

Sabine Van Huffel

KU Leuven

Publications: 131

Bart De Moor

Bart De Moor

KU Leuven

Publications: 111

Amir H. Mohammadi

Amir H. Mohammadi

University of KwaZulu-Natal

Publications: 107

Bart Preneel

Bart Preneel

KU Leuven

Publications: 98

Andrzej Cichocki

Andrzej Cichocki

Skolkovo Institute of Science and Technology

Publications: 90

Yong He

Yong He

Zhejiang University

Publications: 88

Guanrong Chen

Guanrong Chen

City University of Hong Kong

Publications: 86

Lieven De Lathauwer

Lieven De Lathauwer

KU Leuven

Publications: 71

Pierre Comon

Pierre Comon

Grenoble Alpes University

Publications: 69

B. De Moor

B. De Moor

KU Leuven

Publications: 66

Da-Wen Sun

Da-Wen Sun

National University of Ireland

Publications: 58

Sabine Van Huffel

Sabine Van Huffel

KU Leuven

Publications: 57

Martin Haardt

Martin Haardt

Ilmenau University of Technology

Publications: 56

Dirk Timmerman

Dirk Timmerman

KU Leuven

Publications: 55

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