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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 36
- Designing full data science pipelines for clinical decision support systems (CDS)From9 Oct 2023 → TodayFunding: Own budget, for example: patrimony, inscription fees, gifts
- Tensor models in kernel machines and deep learningFrom1 Oct 2023 → TodayFunding: Own budget, for example: patrimony, inscription fees, gifts
- 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
- IMPULS-AI-2021From1 Jan 2021 → 31 Dec 2023Funding: Department General Affairs and Finance
- 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-EU.2.3.-INDUSTRIAL LEADERSHIP - Innovation in SMEs
- End-user interpretability for complex machine learning modelsFrom11 Oct 2019 → 11 Oct 2023Funding: Own budget, for example: patrimony, inscription fees, gifts
- Constraining Model-Free Reinforcement Learning Algorithms with an Application to Autonomous DrivingFrom24 Sep 2019 → 24 Sep 2023Funding: Own budget, for example: patrimony, inscription fees, gifts
- Optimization Frameworks for Deep Kernel MachinesFrom9 Sep 2019 → 21 Dec 2023Funding: Own budget, for example: patrimony, inscription fees, gifts
Publications
21 - 30 of 408
- 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, Panos 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 - Outlier detection in non-elliptical data by kernel MRCD.(2021)
Authors: Joachim Schreurs, Mia Hubert, Johan Suykens, Peter Rousseeuw
- Random Features for Kernel Approximation: A Survey in Algorithms, Theory, and Beyond.(2021)
Authors: Fanghui Liu, Johan Suykens
- Boosting Co-teaching with Compression Regularization for Label Noise(2021)
Authors: Yingyi Chen, Johan Suykens
Pages: 2682 - 2686 - Learning with continuous piecewise linear decision trees(2021)
Authors: Johan Suykens
- Fast Learning in Reproducing Kernel Krein Spaces via Signed Measures(2021)
Authors: Fanghui Liu, Yingyi Chen, Johan Suykens
- Tensor-based Restricted Kernel Machines for Multi-View Classification(2021)
Authors: Lynn Houthuys, Johan Suykens
Pages: 54 - 66 - Generative restricted Kernel machines : A framework for Multi-view Generation and disentangled feature learning(2021)
Authors: Arun Pandey, Joachim Schreurs, Johan Suykens
Pages: 177 - 191