| 2025 | ESANN | Generative Kernel Spectral Clustering. | Sonny Achten, David Winant, Johan A. K. Suykens |
| 2025 | ICANN | HeNCler: Node Clustering in Heterophilous Graphs via Learned Asymmetric Similarity. | Sonny Achten, Zander Op de Beeck, Francesco Tonin, Volkan Cevher, Johan A. K. Suykens |
| 2025 | ICML | Accelerating Spectral Clustering under Fairness Constraints. | Francesco Tonin, Alex Lambert, Johan A. K. Suykens, Volkan Cevher |
| 2024 | AAAI | Unsupervised Neighborhood Propagation Kernel Layers for Semi-supervised Node Classification. | Sonny Achten, Francesco Tonin, Panagiotis Patrinos, Johan A. K. Suykens |
| 2024 | ESANN | Feature Learning using Multi-view Kernel Partial Least Squares. | Xinjie Zeng, Qinghua Tao, Johan A. K. Suykens |
| 2024 | ICML | Self-Attention through Kernel-Eigen Pair Sparse Variational Gaussian Processes. | Yingyi Chen, Qinghua Tao, Francesco Tonin, Johan A. K. Suykens |
| 2024 | ICML | Learning in Feature Spaces via Coupled Covariances: Asymmetric Kernel SVD and Nystrm method. | Qinghua Tao, Francesco Tonin, Alex Lambert, Yingyi Chen, Panagiotis Patrinos, Johan A. K. Suykens |
| 2023 | CVPR | Unbalanced Optimal Transport: A Unified Framework for Object Detection. | Henri De Plaen, Pierre-Franois De Plaen, Johan A. K. Suykens, Marc Proesmans, Tinne Tuytelaars, Luc Van Gool |
| 2023 | ICASSP | Tensorized LSSVMS For Multitask Regression. | Jiani Liu, Qinghua Tao, Ce Zhu, Yipeng Liu, Johan A. K. Suykens |
| 2023 | ICML | Extending Kernel PCA through Dualization: Sparsity, Robustness and Fast Algorithms. | Francesco Tonin, Alex Lambert, Panagiotis Patrinos, Johan A. K. Suykens |
| 2022 | ESANN | Recurrent Restricted Kernel Machines for Time-series Forecasting. | Arun Pandey, Hannes De Meulemeester, Henri De Plaen, Bart De Moor, Johan A. K. Suykens |
| 2021 | AISTATS | Fast Learning in Reproducing Kernel Krein Spaces via Signed Measures. | Fanghui Liu, Xiaolin Huang, Yingyi Chen, Johan A. K. Suykens |
| 2021 | AISTATS | Kernel regression in high dimensions: Refined analysis beyond double descent. | Fanghui Liu, Zhenyu Liao, Johan A. K. Suykens |
| 2021 | CVPR | Boosting Co-Teaching With Compression Regularization for Label Noise. | Yingyi Chen, Xi Shen, Shell Xu Hu, Johan A. K. Suykens |
| 2021 | IJCNN | Unsupervised Energy-based Out-of-distribution Detection using Stiefel-Restricted Kernel Machine. | Francesco Tonin, Arun Pandey, Panagiotis Patrinos, Johan A. K. Suykens |
| 2021 | TIME | Kernel Machines in Time (Invited Talk). | Johan A. K. Suykens |
| 2020 | AAAI | Random Fourier Features via Fast Surrogate Leverage Weighted Sampling. | Fanghui Liu, Xiaolin Huang, Yudong Chen, Jie Yang, Johan A. K. Suykens |
| 2020 | ESANN | Learning from partially labeled data. | Siamak Mehrkanoon, Xiaolin Huang, Johan A. K. Suykens |
| 2020 | IJCNN | Wasserstein Exponential Kernels. | Henri De Plaen, Michal Fanuel, Johan A. K. Suykens |
| 2019 | ICANN | Axiomatic Kernels on Graphs for Support Vector Machines. | Marcin Orchel, Johan A. K. Suykens |
| 2018 | AISTATS | Solving lp-norm regularization with tensor kernels. | Saverio Salzo, Lorenzo Rosasco, Johan A. K. Suykens |
| 2018 | ESANN | Shallow and Deep Models for Domain Adaptation problems. | Siamak Mehrkanoon, Matthew B. Blaschko, Johan A. K. Suykens |
| 2018 | ESANN | Generative Kernel PCA. | Joachim Schreurs, Johan A. K. Suykens |
| 2018 | ICANN | Tensor Learning in Multi-view Kernel PCA. | Lynn Houthuys, Johan A. K. Suykens |
| 2018 | ICANN | Weighted Multi-view Deep Neural Networks for Weather Forecasting. | Zahra Karevan, Lynn Houthuys, Johan A. K. Suykens |
| 2017 | ESANN | Moving Least Squares Support Vector Machines for weather temperature prediction. | Zahra Karevan, Yunlong Feng, Johan A. K. Suykens |
| 2017 | ESANN | Scalable Hybrid Deep Neural Kernel Networks. | Siamak Mehrkanoon, Andreas Zell, Johan A. K. Suykens |
| 2017 | IJCNN | Probabilistic matrix factorization from quantized measurements. | Giulio Bottegal, Johan A. K. Suykens |
| 2017 | IJCNN | Multi-view LS-SVM regression for black-box temperature prediction in weather forecasting. | Lynn Houthuys, Zahra Karevan, Johan A. K. Suykens |
| 2016 | CIARP | Efficient Sparse Approximation of Support Vector Machines Solving a Kernel Lasso. | Marcelo Aliquintuy, Emanuele Frandi, Ricardo anculef, Johan A. K. Suykens |
| 2016 | ESANN | Clustering from two data sources using a kernel-based approach with weight coupling. | Lynn Houthuys, Rocco Langone, Johan A. K. Suykens |
| 2016 | ESANN | Spatio-temporal feature selection for black-box weather forecasting. | Zahra Karevan, Johan A. K. Suykens |
| 2016 | ESANN | Fast in-memory spectral clustering using a fixed-size approach. | Rocco Langone, Raghvendra Mall, Vilen Jumutc, Johan A. K. Suykens |
| 2016 | IJCNN | Clustering-based feature selection for black-box weather temperature prediction. | Zahra Karevan, Johan A. K. Suykens |
| 2016 | IJCNN | Denoised Kernel Spectral data Clustering. | Raghvendra Mall, Halima Bensmail, Rocco Langone, Carolina Varon, Johan A. K. Suykens |
| 2016 | IJCNN | Multi-label semi-supervised learning using regularized kernel spectral clustering. | Siamak Mehrkanoon, Johan A. K. Suykens |
| 2015 | ESANN | Ranking Overlap and Outlier Points in Data using Soft Kernel Spectral Clustering. | Raghvendra Mall, Rocco Langone, Johan A. K. Suykens |
| 2015 | IJCNN | A PARTAN-accelerated Frank-Wolfe algorithm for large-scale SVM classification. | Emanuele Frandi, Ricardo anculef, Johan A. K. Suykens |
| 2015 | IJCNN | Black-box modeling for temperature prediction in weather forecasting. | Zahra Karevan, Siamak Mehrkanoon, Johan A. K. Suykens |
| 2015 | IJCNN | Kernel spectral document clustering using unsupervised precision-recall metrics. | Raghvendra Mall, Johan A. K. Suykens |
| 2015 | IJCNN | Hierarchical semi-supervised clustering using KSC based model. | Siamak Mehrkanoon, Oscar Mauricio Agudelo, Raghvendra Mall, Johan A. K. Suykens |
| 2014 | CIDM | New bilinear formulation to semi-supervised classification based on Kernel Spectral Clustering. | Vilen Jumutc, Johan A. K. Suykens |
| 2014 | CIDM | Alarm prediction in industrial machines using autoregressive LS-SVM models. | Rocco Langone, Carlos Alzate, Abdellatif Bey-Temsamani, Johan A. K. Suykens |
| 2014 | CIDM | Clustering data over time using kernel spectral clustering with memory. | Rocco Langone, Raghvendra Mall, Johan A. K. Suykens |
| 2014 | CIDM | Agglomerative hierarchical kernel spectral data clustering. | Raghvendra Mall, Rocco Langone, Johan A. K. Suykens |
| 2014 | ESANN | Reweighted l1 Dual Averaging Approach for Sparse Stochastic Learning. | Vilen Jumutc, Johan A. K. Suykens |
| 2014 | ESANN | Agglomerative hierarchical kernel spectral clustering for large scale networks. | Raghvendra Mall, Rocco Langone, Johan A. K. Suykens |
| 2014 | ESANN | Optimal Data Projection for Kernel Spectral Clustering. | Diego Hernn Peluffo-Ordez, Carlos Alzate, Johan A. K. Suykens, Germn Castellanos-Domnguez |
| 2014 | IJCNN | SVD truncation schemes for fixed-size kernel models. | Ricardo Castro-Garcia, Siamak Mehrkanoon, Anna Marconato, Johan Schoukens, Johan A. K. Suykens |
| 2014 | IJCNN | Optimal reduced sets for sparse kernel spectral clustering. | Raghvendra Mall, Siamak Mehrkanoon, Rocco Langone, Johan A. K. Suykens |
| 2014 | IJCNN | Large scale semi-supervised learning using KSC based model. | Siamak Mehrkanoon, Johan A. K. Suykens |
| 2014 | ISNN | Reweighted l 2-Regularized Dual Averaging Approach for Highly Sparse Stochastic Learning. | Vilen Jumutc, Johan A. K. Suykens |
| 2013 | CIDM | Supervised Novelty Detection. | Vilen Jumutc, Johan A. K. Suykens |
| 2013 | CIDM | Kernel spectral clustering for predicting maintenance of industrial machines. | Rocco Langone, Carlos Alzate, Bart De Ketelaere, Johan A. K. Suykens |
| 2013 | COMAD | Primal-Dual Framework for Feature Selection using Least Squares Support Vector Machines. | Raghvendra Mall, Johan A. K. Suykens, Mohammed El Anbari, Halima Bensmail |
| 2013 | IJCNN | Fixed-size Pegasos for hinge and pinball loss SVM. | Vilen Jumutc, Xiaolin Huang, Johan A. K. Suykens |
| 2013 | IJCNN | Soft kernel spectral clustering. | Rocco Langone, Raghvendra Mall, Johan A. K. Suykens |
| 2013 | IJCNN | Non-parallel semi-supervised classification based on kernel spectral clustering. | Siamak Mehrkanoon, Johan A. K. Suykens |
| 2013 | IJCNN | Kernel spectral clustering for dynamic data using multiple kernel learning. | Diego Hernn Peluffo-Ordez, Sergio Garca-Vega, Rocco Langone, Johan A. K. Suykens, Germn Castellanos-Domnguez |
| 2013 | PAKDD | Sparse Reductions for Fixed-Size Least Squares Support Vector Machines on Large Scale Data. | Raghvendra Mall, Johan A. K. Suykens |
| 2013 | UIST | The skweezee system: enabling the design and the programming of squeeze interactions. | Karen Vanderloock, Vero Vanden Abeele, Johan A. K. Suykens, Luc Geurts |
| 2012 | ESANN | Interval coded scoring systems for survival analysis. | Vanya Van Belle, Sabine Van Huffel, Johan A. K. Suykens, Stephen P. Boyd |
| 2012 | ESANN | Joint Regression and Linear Combination of Time Series for Optimal Prediction. | Dries Geebelen, Kim Batselier, Philippe Dreesen, Marco Signoretto, Johan A. K. Suykens, Bart De Moor, Joos Vandewalle |
| 2012 | IJCNN | A semi-supervised formulation to binary kernel spectral clustering. | Carlos Alzate, Johan A. K. Suykens |
| 2012 | IJCNN | Robustness of kernel based regression: Influence and weight functions. | Kris De Brabanter, Jos De Brabanter, Johan A. K. Suykens, Joos Vandewalle, Bart De Moor |
| 2012 | IJCNN | Kernel spectral clustering for community detection in complex networks. | Rocco Langone, Carlos Alzate, Johan A. K. Suykens |
| 2011 | ESANN | Sparse LS-SVMs with L0 - norm minimization. | Jorge Lpez Lzaro, Kris De Brabanter, Jos R. Dorronsoro, Johan A. K. Suykens |
| 2011 | ESANN | Symbolic computing of LS-SVM based models. | Siamak Mehrkanoon, Li Jiang, Carlos Alzate, Johan A. K. Suykens |
| 2011 | ICANN | Automatic Seizure Detection Incorporating Structural Information. | Borbla Hunyadi, Maarten De Vos, Marco Signoretto, Johan A. K. Suykens, Wim Van Paesschen, Sabine Van Huffel |
| 2011 | IJCNN | Out-of-sample eigenvectors in kernel spectral clustering. | Carlos Alzate, Johan A. K. Suykens |
| 2011 | IJCNN | Modularity-based model selection for kernel spectral clustering. | Rocco Langone, Carlos Alzate, Johan A. K. Suykens |
| 2010 | ESANN | Highly sparse kernel spectral clustering with predictive out-of-sample extensions. | Carlos Alzate, Johan A. K. Suykens |
| 2010 | ESANN | On the use of a clinical kernel in survival analysis. | Vanya Van Belle, Kristiaan Pelckmans, Johan A. K. Suykens, Sabine Van Huffel |
| 2010 | ICANN | Kernel-Based Learning from Infinite Dimensional 2-Way Tensors. | Marco Signoretto, Lieven De Lathauwer, Johan A. K. Suykens |
| 2010 | IJCNN | Polynomial componentwise LS-SVM: Fast variable selection using low rank updates. | Fabian Ojeda, Tillmann Falck, Bart De Moor, Johan A. K. Suykens |
| 2009 | CBMS | Differentiation between brain metastases and glioblastoma multiforme based on MRI, MRS and MRSI. | Jan Luts, Johan A. K. Suykens, Sabine Van Huffel, Teresa Laudadio, Sofie Van Cauter, Uwe Himmelreich, Enrique Molla, Jose Piquer, M. Carmen Martnez-Bisbal, Bernardo Celda |
| 2009 | ESANN | Transductively Learning from Positive Examples Only. | Kristiaan Pelckmans, Johan A. K. Suykens |
| 2009 | ICANN | Identifying Customer Profiles in Power Load Time Series Using Spectral Clustering. | Carlos Alzate, Marcelo Espinoza, Bart De Moor, Johan A. K. Suykens |
| 2009 | ICANN | MINLIP: Efficient Learning of Transformation Models. | Vanya Van Belle, Kristiaan Pelckmans, Johan A. K. Suykens, Sabine Van Huffel |
| 2009 | ICANN | Robustness of Kernel Based Regression: A Comparison of Iterative Weighting Schemes. | Kris De Brabanter, Kristiaan Pelckmans, Jos De Brabanter, Michiel Debruyne, Johan A. K. Suykens, Mia Hubert, Bart De Moor |
| 2009 | ICMLA | Feature Extraction and Classification of EEG Signals for Rapid P300 Mind Spelling. | Adrien Combaz, Nikolay V. Manyakov, Nikolay Chumerin, Johan A. K. Suykens, Marc M. Van Hulle |
| 2009 | IJCNN | A regularized formulation for spectral clustering with pairwise constraints. | Carlos Alzate, Johan A. K. Suykens |
| 2009 | IWANN | Feature Selection in Survival Least Squares Support Vector Machines with Maximal Variation Constraints. | Vanya Van Belle, Kristiaan Pelckmans, Johan A. K. Suykens, Sabine Van Huffel |
| 2009 | KI | P300 Detection Based on Feature Extraction in On-line Brain-Computer Interface. | Nikolay Chumerin, Nikolay V. Manyakov, Adrien Combaz, Johan A. K. Suykens, Refet Firat Yazicioglu, Tom Torfs, Patrick Merken, Herc P. Neves, Chris Van Hoof, Marc M. Van Hulle |
| 2008 | ESANN | Survival SVM: a practical scalable algorithm. | Vanya Van Belle, Kristiaan Pelckmans, Johan A. K. Suykens, Sabine Van Huffel |
| 2008 | ICANN | Quadratically Constrained Quadratic Programming for Subspace Selection in Kernel Regression Estimation. | Marco Signoretto, Kristiaan Pelckmans, Johan A. K. Suykens |
| 2008 | IJCNN | Sparse kernel models for spectral clustering using the incomplete Cholesky decomposition. | Carlos Alzate, Johan A. K. Suykens |
| 2007 | ESANN | Convex optimization for the design of learning machines. | Kristiaan Pelckmans, Johan A. K. Suykens, Bart De Moor |
| 2007 | ICANN | Comparing Methods for Multi-class Probabilities in Medical Decision Making Using LS-SVMs and Kernel Logistic Regression. | Ben Van Calster, Jan Luts, Johan A. K. Suykens, George Condous, Tom Bourne, Dirk Timmerman, Sabine Van Huffel |
| 2007 | ICASSP | State-of-the-Art and Evolution in Public Data Sets and Competitions for System Identification, Time Series Prediction and Pattern Recognition. | Joos Vandewalle, Johan A. K. Suykens, Bart De Moor, Amaury Lendasse |
| 2007 | IJCNN | ICA through an LS-SVM based Kernel CCA Measure for Independence. | Carlos Alzate, Johan A. K. Suykens |
| 2007 | IJCNN | Multi-class kernel logistic regression: a fixed-size implementation. | Peter Karsmakers, Kristiaan Pelckmans, Johan A. K. Suykens |
| 2007 | IJCNN | Variable selection by rank-one updates for least squares support vector machines. | Fabian Ojeda, Johan A. K. Suykens, Bart De Moor |
| 2007 | Interspeech | Fixed-size kernel logistic regression for phoneme classification. | Peter Karsmakers, Kristiaan Pelckmans, Johan A. K. Suykens, Hugo Van hamme |
| 2006 | IJCNN | A Weighted Kernel PCA Formulation with Out-of-Sample Extensions for Spectral Clustering Methods. | Carlos Alzate, Johan A. K. Suykens |
| 2006 | ISCAS | Multi-scroll and hypercube attractors from Josephson junctions. | Mstak E. Yalin, Johan A. K. Suykens, Joos Vandewalle |
| 2005 | ICANN | Componentwise Support Vector Machines for Structure Detection. | Kristiaan Pelckmans, Johan A. K. Suykens, Bart De Moor |
| 2005 | IJCNN | Extending kernel principal component analysis to general underlying loss functions. | Carlos Alzate, Johan A. K. Suykens |
| 2005 | IJCNN | Maximal variation and missing values for componentwise support vector machines. | Kristiaan Pelckmans, Johan A. K. Suykens, Bart De Moor, Jos De Brabanter |
| 2005 | ISCAS | Spatiotemporal pattern formation in the ACE16k CNN chip. | Mstak E. Yalin, Johan A. K. Suykens, Joos Vandewalle |
| 2005 | IWANN | Load Forecasting Using Fixed-Size Least Squares Support Vector Machines. | Marcelo Espinoza, Johan A. K. Suykens, Bart De Moor |
| 2004 | ESANN | Sparse LS-SVMs using additive regularization with a penalized validation criterion. | Kristiaan Pelckmans, Johan A. K. Suykens, Bart De Moor |
| 2004 | ICONIP | A Comparison of Pruning Algorithms for Sparse Least Squares Support Vector Machines. | Luc Hoegaerts, Johan A. K. Suykens, Joos Vandewalle, Bart De Moor |
| 2004 | ICONIP | Morozov, Ivanov and Tikhonov Regularization Based LS-SVMs. | Kristiaan Pelckmans, Johan A. K. Suykens, Bart De Moor |
| 2004 | IJCNN | Primal space sparse kernel partial least squares regression for large scale problems. | Luc Hoegaerts, Johan A. K. Suykens, Joos Vandewalle, Bart De Moor |
| 2004 | IJCNN | Regularization constants in LS-SVMs: a fast estimate via convex optimization. | Kristiaan Pelckmans, Johan A. K. Suykens, Bart De Moor |
| 2004 | ISCAS | A double scroll based true random bit generator. | Mstak E. Yalin, Johan A. K. Suykens, Joos Vandewalle |
| 2004 | SSPR | Learning from General Label Constraints. | Tijl De Bie, Johan A. K. Suykens, Bart De Moor |
| 2003 | AIME | Classification of Ovarian Tumors Using Bayesian Least Squares Support Vector Machines. | Chuan Lu, Tony Van Gestel, Johan A. K. Suykens, Sabine Van Huffel, Dirk Timmerman, Ignace Vergote |
| 2003 | ESANN | Kernel PLS variants for regression. | Luc Hoegaerts, Johan A. K. Suykens, Joos Vandewalle, Bart De Moor |
| 2003 | ISCAS | Coupled chaotic simulated annealing processes. | Johan A. K. Suykens, Mstak E. Yalin, Joos Vandewalle |
| 2002 | ESANN | Prediction of mental development of preterm newborns at birth time using LS-SVM. | Lieveke Ameye, Chuan Lu, Lukas Lukas, Jos De Brabanter, Johan A. K. Suykens, Sabine Van Huffel, Hans Daniels, Gunnar Naulaers, Hugo Devlieger |
| 2002 | ESANN | The use of LS-SVM in the classification of brain tumors based on Magnetic Resonance Spectroscopy signals. | Lukas Lukas, Andy Devos, Johan A. K. Suykens, Leentje Vanhamme, Sabine Van Huffel, Anne Rosemary Tate, Carles Majs, Carles Ars |
| 2002 | ICANN | Robust Cross-Validation Score Function for Non-linear Function Estimation. | Jos De Brabanter, Kristiaan Pelckmans, Johan A. K. Suykens, Joos Vandewalle |
| 2002 | ICANN | Compactly Supported RBF Kernels for Sparsifying the Gram Matrix in LS-SVM Regression Models. | Bart Hamers, Johan A. K. Suykens, Bart De Moor |
| 2001 | ESANN | Automatic relevance determination for Least Squares Support Vector Machines classifiers. | Tony Van Gestel, Johan A. K. Suykens, Bart De Moor, Joos Vandewalle |
| 2001 | ICANN | Kernel Canonical Correlation Analysis and Least Squares Support Vector Machines. | Tony Van Gestel, Johan A. K. Suykens, Jos De Brabanter, Bart De Moor, Joos Vandewalle |
| 2000 | ESANN | Sparse least squares Support Vector Machine classifiers. | Johan A. K. Suykens, Lukas Lukas, Joos Vandewalle |
| 2000 | ESANN | The K.U.Leuven competition data: a challenge for advanced neural network techniques. | Johan A. K. Suykens, Joos Vandewalle |
| 2000 | ISCAS | Sparse approximation using least squares support vector machines. | Johan A. K. Suykens, Lukas Lukas, Joos Vandewalle |
| 2000 | KES | An empirical assessment of kernel type performance for least squares support vector machine classifiers. | Bart Baesens, Stijn Viaene, Tony Van Gestel, Johan A. K. Suykens, Guido Dedene, Bart De Moor, Jan Vanthienen |
| 1999 | IJCNN | Multiclass least squares support vector machines. | Johan A. K. Suykens, Joos Vandewalle |
| 1999 | IJCNN | Continuous time NLq theory: absolute stability criteria. | Johan A. K. Suykens, Joos Vandewalle |
| 1999 | ISCAS | On the realization of n-scroll attractors. | Mstak E. Yalin, Johan A. K. Suykens, Joos Vandewalle |
| 1998 | ESANN | Improved generalization ability of neurocontrollers by imposing NLq stability constraints. | Johan A. K. Suykens, Joos Vandewalle |
| 1995 | ESANN | NLq theory: unifications in the theory of neural networks, systems and control. | Johan A. K. Suykens, Bart De Moor, Joos Vandewalle |
| 1995 | ISCAS | Generalized Cellular Neural Networks Represented in he NL | Johan A. K. Suykens, Joos Vandewalle |