Publications

• Determinantal Point Processes Implicitly Regularize Semi-parametric Regression Problems

  Michaël Fanuel, Joachim Schreurs, and Johan AK Suykens - SIAM Journal on Mathematics of Data Science (SIMODS), 2022

• Nyström Landmark Sampling and Regularized Christoffel Functions

  Michaël Fanuel, Joachim Schreurs, and Johan AK Suykens - Machine Learning, 2022

• Disentangled Representation Learning and Generation with Manifold Optimization

  Arun Pandey, Michaël Fanuel, Joachim Schreurs, and Johan AK Suykens - Neural Computation, 2022

• Island Transpeciation: A Co-Evolutionary Neural Architecture Search, applied to country-scale air-quality forecasting

  Konstantinos Theodorakos, Oscar Mauricio Agudelo Manozca, Joachim Schreurs, Johan AK Suykens, and Bart De Moor - IEEE Transactions On Evolutionary Computation, 2022

• Outlier Detection in Non-Elliptical Data by Kernel MRCD

  Joachim Schreurs, Iwein Vranckx, Bart De Ketelaere, Mia Hubert, Johan A.K. Suykens, and Peter J. Rousseeuw - Statistics and Computing, 2021

• Leverage Score Sampling for Complete Mode Coverage in Generative Adversarial Networks

  Joachim Schreurs, Hannes De Meulemeester, Michaël Fanuel, Bart De Moor, and Johan AK Suykens - International Conference on Machine Learning, Optimization, and Data Science (LOD) 2021

• The Bures Metric for Generative Adversarial Networks

  Hannes De Meulemeester, Joachim Schreurs, Michaël Fanuel, Bart De Moor, and Johan AK Suykens - European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD) 2021

• Ensemble Kernel Methods, Implicit Regularization and Determinantal Point Processes

  Joachim Schreurs, Michaël Fanuel, and Johan AK Suykens - ICML Workshop on Negative Dependence and Submodularity in Machine Learning 2020

• Robust Generative Restricted Kernel Machines using Weighted Conjugate Feature Duality

  Arun Pandey, Joachim Schreurs, and Johan AK Suykens - International Conference on Machine Learning, Optimization, and Data Science (LOD) 2020

• Diversity Sampling is an Implicit Regularization for Kernel Methods

  Michaël Fanuel, Joachim Schreurs, and Johan AK Suykens - SIAM Journal on Mathematics of Data Science (SIMODS) 2020

• Generative Restricted Kernel Machines: A Framework for Multi-view Generation and Disentangled Feature Learning

  Arun Pandey, Joachim Schreurs, and Johan AK Suykens - Neural Networks 2020

• Latent Space Exploration using Generative Kernel PCA

  David Winant, Joachim Schreurs, and Johan AK Suykens - Belgian Dutch Conference on Machine Learning BNAIC/Benelearn 2019

• Towards Deterministic Diverse Subset Sampling

  Joachim Schreurs, Michaël Fanuel, and Johan AK Suykens - Belgian Dutch Conference on Machine Learning BNAIC/Benelearn 2019

• Generative Kernel PCA

  Joachim Schreurs, and Johan AK Suykens - European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN) 2018