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Researcher
Johan Suykens
- Disciplines:Modelling, Applied mathematics in specific fields, Computer architecture and networks, Information sciences, Information systems, Programming languages, Scientific computing, Theoretical computer science, Visual computing, Other information and computing sciences, Control systems, robotics and automation, Design theories and methods, Mechatronics and robotics, Biological system engineering, Computer theory, Signal processing
Affiliations
- Dynamical Systems, Signal Processing and Data Analytics (STADIUS) (Division)
Member
From1 Aug 2020 → Today - ESAT - STADIUS, Stadius Centre for Dynamical Systems, Signal Processing and Data Analytics (Division)
Member
From1 Jan 2008 → 31 Jul 2020 - Faculty of Engineering Science (Faculty)
Member
From1 Oct 2000 → 30 Sep 2003 - Department of Electrical Engineering (ESAT) (Department)
Member
From1 Oct 1999 → 31 Dec 2007
Projects
1 - 10 of 32
- Tensor Tools for Taming the CurseFrom1 Jan 2023 → TodayFunding: BOF - iBOF
- Duality model-based approaches to clusteringFrom27 Sep 2021 → TodayFunding: Own budget, for example: patrimony, inscription fees, gifts
- AI-based Model FusionFrom5 Oct 2020 → TodayFunding: Own budget, for example: patrimony, inscription fees, gifts
- Foundations of Trustworthy AI - Integrating Reasoning, Learning and OptimizationFrom1 Sep 2020 → TodayFunding: H2020 - Innovation in SMEs
- End-user interpretability for complex machine learning modelsFrom11 Oct 2019 → TodayFunding: Own budget, for example: patrimony, inscription fees, gifts
- Stability Analysis and Performance Improvement of Deep Reinforcement Learning AlgorithmsFrom24 Sep 2019 → TodayFunding: Own budget, for example: patrimony, inscription fees, gifts
- Geometric Deep Learning and Kernel Method: Theory and ApplicationsFrom18 Feb 2019 → 18 Feb 2023Funding: Own budget, for example: patrimony, inscription fees, gifts
- Large scale algorithms for data-driven modelling: duality, stability and generalization propertiesFrom28 Jan 2019 → 28 Jan 2023Funding: Own budget, for example: patrimony, inscription fees, gifts
- Representation Learning with Restricted Kernel MachinesFrom8 Nov 2018 → 8 Nov 2022Funding: Own budget, for example: patrimony, inscription fees, gifts
- Exploring Duality for Future Data-driven ModellingFrom1 Oct 2018 → TodayFunding: H2020 - Frontier Research (ERC)
Publications
1 - 10 of 346
- Jigsaw-ViT: Learning Jigsaw Puzzles in Vision Transformer(2023)
Authors: Yingyi Chen, Johan Suykens
Pages: 53 - 60 - Towards a Unified Quadrature Framework for Large-Scale Kernel Machines(2022)
Authors: Fanghui Liu, Johan Suykens
Pages: 7975 - 7988 - Piecewise Linear Neural Networks and Deep Learning(2022)
Authors: Johan Suykens
- Improved Update Rule and Sampling of Stochastic Gradient Descent with Extreme Early Stopping for Support Vector Machines(2022)
Authors: Johan Suykens
Pages: 147 - 161Number of pages: 15 - Transfer Learning in Demand Response: a Review of Algorithms for Data-efficient Modelling and Control(2022)
Authors: Thijs Peirelinck, Hussain Syed Kazmi, Johan Suykens, Geert Deconinck
- Nystrom landmark sampling and regularized Christoffel functions(2022)
Authors: Michaël Fanuel, Joachim Schreurs, Johan Suykens
Pages: 2213 - 2254 - Positive semi-definite embedding for dimensionality reduction and out-of-sample extensions.(2022)
Authors: Johan Suykens
Pages: 153 - 178 - A novel neural grey system model with Bayesian regularization and its applications(2021)
Authors: Johan Suykens
Pages: 61 - 75 - Unsupervised learning of disentangled representations in deep restricted kernel machines with orthogonality constraints(2021)
Authors: Francesco Tonin, Panagiotis Patrinos, Johan Suykens
Pages: 661 - 679 - Leverage Score Sampling for Complete Mode Coverage in Generative Adversarial Networks(2021)
Authors: Joachim Schreurs, Hannes De Meulemeester, Michaël Fanuel, Bart De Moor, Johan Suykens
Pages: 466 - 480