Exploring Duality for Future Data-driven Modelling

Duality in Multi-View Restricted Kernel Machines

Author(s): Achten, Sonny; Pandey, Arun; De Meulemeester, Hannes; De Moor, Bart; Suykens, Johan A. K.
Published in: ICML Workshop on Duality for Modern Machine Learning,, Issue 5, 2023
Publisher: ICML
DOI: 10.48550/arxiv.2305.17251

A Dual Formulation for Probabilistic Principal Component Analysis

Author(s): De Plaen, Henri; Suykens, J
Published in: Proceedings ol ICML 2023 Workshop on Duality Principles for Modern Machine Learning (DP4ML);, Issue 1, 2023
Publisher: DP4ML
DOI: 10.48550/arxiv.2307.10078

Extending Kernel PCA through Dualization: Sparsity, Robustness and Fast Algorithms

Author(s): Tonin, Francesco; Lambert, A; Patrinos, P; Suykens, J
Published in: International Conference on Machine Learning (ICML 2023), 2023
Publisher: PMLR 202

Unsupervised Energy-based Out-of-distribution Detection using Stiefel-Restricted Kernel Machine

Author(s): Tonin, Francesco; Pandey, Arun; Patrinos, Panagiotis; Suykens, Johan A. K.
Published in: International Joint Conference on Neural Networks, Issue 4, 2021, ISSN 2161-4393
Publisher: Institute of Electrical and Electronics Engineers
DOI: 10.1109/ijcnn52387.2021.9533706

A Theoretical Framework for Target Propagation

Author(s): Meulemans, Alexander; Carzaniga, Francesco; Suykens, Johan A.K.; Sacramento, João; Grewe, Benjamin F.
Published in: Advances in Neural Information Processing Systems, Issue 33, 2020, Page(s) 20024--20036
Publisher: NeurIPS
DOI: 10.5167/uzh-198834

Recurrent Restricted Kernel Machines for Time-series Forecasting

Author(s): Pandey, A; De Meulemeester, H; De Plaen, H; De Moor, B; Suykens, Johan
Published in: European symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, Issue ESANN 2022, 2022
Publisher: ESANN

Boosting Co-teaching with Compression Regularization for Label Noise

Author(s): Yingyi Chen, Xi Shen, Shell Xu Hu, Johan A. K. Suykens
Published in: 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), 2021, Page(s) 2682-2686, ISBN 978-1-6654-4899-4
Publisher: IEEE
DOI: 10.1109/cvprw53098.2021.00302

Unsupervised Neighborhood Propagation Kernel Layers for Semi-supervised Node Classification

Author(s): Achten, Sonny; Tonin, F; Patrinos, Panagiotis; Suykens, J
Published in: AAAI Conference on Artificial Intelligence, Issue 2024, 2024, ISBN 1-57735-887-2
Publisher: AAAI Press
DOI: 10.1609/aaai.v38i10.28949

The Bures Metric for Generative Adversarial Networks

Author(s): De Meulemeester, Hannes; Schreurs, Joachim; Fanuel, Michaël; De Moor, Bart; Suykens, Johan A. K.
Published in: The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, 2021
Publisher: ECML-PKDD 2021

Ensemble Kernel Methods, Implicit Regularization and Determinantal Point Processes

Author(s): Schreurs, Joachim; Fanuel, M; Suykens, J
Published in: ICML 2020 Workshop on Negative Dependence and Submodularity for ML, Issue 15, 2020
Publisher: ICML

Wasserstein Exponential Kernels

Author(s): Henri De Plaen, Michael Fanuel, Johan A. K. Suykens
Published in: 2020 International Joint Conference on Neural Networks (IJCNN), 2020, Page(s) 1-6, ISBN 978-1-7281-6926-2
Publisher: IEEE
DOI: 10.1109/ijcnn48605.2020.9207630

Leverage Score Sampling for Complete Mode Coverage in Generative Adversarial Networks

Author(s): Schreurs J., De Meulemeester H., Fanuel M., De Moor B., Suykens J.A.K
Published in: Conference on Machine Learning, Optimization and Data Science, 2021, ISBN 978-3-030-95469-7
Publisher: Springer
DOI: 10.1007/978-3-030-95470-3_35

On the Double Descent of Random Features Models Trained with SGD

Author(s): Liu, F; Suykens, Johan; Cevher, V
Published in: Advances in Neural Information Processing Systems 35 (NeurIPS 2022), 2022, ISBN 9781713871088
Publisher: NeurIPS

Tensorized LSSVMs for Multitask Regression

Author(s): Liu, J; Tao, Q; Zhu, C; Liu, Y; Suykens, Johan
Published in: IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2023), 2023, ISBN 978-1-7281-6327-7
Publisher: IEEE
DOI: 10.1109/icassp49357.2023.10094580

Fast Adaptive Hinging Hyperplanes

Author(s): Qinghua Tao, Jun Xu, Johan A.K. Suykens, Shuning Wang
Published in: 2018 IEEE Conference on Decision and Control (CDC), 2018, Page(s) 1482-1487, ISBN 978-1-5386-1395-5
Publisher: IEEE
DOI: 10.1109/cdc.2018.8619653

Fast Learning in Reproducing Kernel Krein Spaces via Signed Measures

Author(s): Fanghui Liu, Xiaolin Huang, Yingyi Chen, Johan Suykens
Published in: roceedings of The 24th International Conference on Artificial Intelligence and Statistics, Issue PMLR 130, 2021, Page(s) 388-396
Publisher: PMLR

Combining Primal and Dual Representations in Deep Restricted Kernel Machines Classifiers

Author(s): Tonin, F; Patrinos, P; Suykens, Johan
Published in: ECML PKDD 2023 - Workshop on Simplification, Compression, Efficiency and Frugality for Artificial intelligence, 2023
Publisher: ECML PKDD

Kernel regression in high dimensions: Refined analysis beyond double descent

Author(s): Fanghui Liu, Zhenyu Liao, Johan Suykens
Published in: Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, Issue PMLR 130, 2021, Page(s) 649-657
Publisher: PMLR

Primal-Attention: Self-attention through Asymmetric Kernel SVD in Primal Representation

Author(s): Chen, Yingyi; Tao, Qinghua; Tonin, Francesco; Suykens, Johan A. K.
Published in: Proc. of NeurIPS 2023, Issue 1, 2023
Publisher: NeuriPS
DOI: 10.48550/arxiv.2305.19798

Unbalanced Optimal Transport: A Unified Framework for Object Detection

Author(s): De Plaen, Henri; De Plaen, P; Suykens, J; Proesmans, M; Tuytelaars, T; Van Gool, L
Published in: Proceedings / CVPR, IEEE Computer Society Conference on Computer Vision and Pattern, Issue 5, 2023, ISSN 1063-6919
Publisher: IEEE
DOI: 10.1109/cvpr52729.2023.00312

The Bures Metric for Generative Adversarial Networks

Author(s): Hannes De Meulemeester, Joachim Schreurs, Michaël Fanuel, Bart De Moor, Johan A. K. Suykens
Published in: Machine Learning and Knowledge Discovery in Databases. Research Track - European Conference, ECML PKDD 2021, Bilbao, Spain, September 13–17, 2021, Proceedings, Part II, Issue 12976, 2021, Page(s) 52-66, ISBN 978-3-030-86519-1
Publisher: Springer International Publishing
DOI: 10.1007/978-3-030-86520-7_4

Latent Space Exploration Using Generative Kernel PCA

Author(s): David Winant, Joachim Schreurs, Johan A. K. Suykens
Published in: Artificial Intelligence and Machine Learning - 31st Benelux AI Conference, BNAIC 2019, and 28th Belgian-Dutch Machine Learning Conference, BENELEARN 2019, Brussels, Belgium, November 6-8, 2019, Revised Selected Papers, Issue 1196, 2020, Page(s) 70-82, ISBN 978-3-030-65153-4
Publisher: Springer International Publishing
DOI: 10.1007/978-3-030-65154-1_5

Robust Generative Restricted Kernel Machines Using Weighted Conjugate Feature Duality

Author(s): Arun Pandey, Joachim Schreurs, Johan A. K. Suykens
Published in: Machine Learning, Optimization, and Data Science - 6th International Conference, LOD 2020, Siena, Italy, July 19–23, 2020, Revised Selected Papers, Part I, Issue 12565, 2020, Page(s) 613-624, ISBN 978-3-030-64582-3
Publisher: Springer International Publishing
DOI: 10.1007/978-3-030-64583-0_54

Towards Deterministic Diverse Subset Sampling

Author(s): J. Schreurs, M. Fanuel, J. A. K. Suykens
Published in: Artificial Intelligence and Machine Learning - 31st Benelux AI Conference, BNAIC 2019, and 28th Belgian-Dutch Machine Learning Conference, BENELEARN 2019, Brussels, Belgium, November 6-8, 2019, Revised Selected Papers, Issue 1196, 2020, Page(s) 137-151, ISBN 978-3-030-65153-4
Publisher: Springer International Publishing
DOI: 10.1007/978-3-030-65154-1_8

Fast Hyperparameter Tuning for Support Vector Machines with Stochastic Gradient Descent

Author(s): Marcin Orchel, Johan A. K. Suykens
Published in: Machine Learning, Optimization, and Data Science - 6th International Conference, LOD 2020, Siena, Italy, July 19–23, 2020, Revised Selected Papers, Part II, Issue 12566, 2020, Page(s) 481-493, ISBN 978-3-030-64579-3
Publisher: Springer International Publishing
DOI: 10.1007/978-3-030-64580-9_40

Tensor Learning in Multi-view Kernel PCA

Author(s): Lynn Houthuys, Johan A. K. Suykens
Published in: Artificial Neural Networks and Machine Learning – ICANN 2018 - 27th International Conference on Artificial Neural Networks, Rhodes, Greece, October 4-7, 2018, Proceedings, Part II, Issue 11140, 2018, Page(s) 205-215, ISBN 978-3-030-01420-9
Publisher: Springer International Publishing
DOI: 10.1007/978-3-030-01421-6_21

Weighted Multi-view Deep Neural Networks for Weather Forecasting

Author(s): Zahra Karevan, Lynn Houthuys, Johan A. K. Suykens
Published in: Artificial Neural Networks and Machine Learning – ICANN 2018 - 27th International Conference on Artificial Neural Networks, Rhodes, Greece, October 4-7, 2018, Proceedings, Part III, Issue 11141, 2018, Page(s) 489-499, ISBN 978-3-030-01423-0
Publisher: Springer International Publishing
DOI: 10.1007/978-3-030-01424-7_48

Axiomatic Kernels on Graphs for Support Vector Machines

Author(s): Marcin Orchel, Johan A. K. Suykens
Published in: Artificial Neural Networks and Machine Learning – ICANN 2019: Workshop and Special Sessions - 28th International Conference on Artificial Neural Networks, Munich, Germany, September 17–19, 2019, Proceedings, Issue 11731, 2019, Page(s) 685-700, ISBN 978-3-030-30492-8
Publisher: Springer International Publishing
DOI: 10.1007/978-3-030-30493-5_62

Low-Rank Multitask Learning based on Tensorized SVMs and LSSVMs

Author(s): Liu, Jiani; Tao, Qinghua; Zhu, Ce; Liu, Yipeng; Huang, Xiaolin; Suykens, Johan A. K.
Published in: Technical report, Issue 1, 2023
Publisher: KU Leuven
DOI: 10.48550/arxiv.2308.16056

Can overfitted deep neural networks in adversarial training generalize? -- An approximation viewpoint

Author(s): Shi, Zhongjie; Liu, Fanghui; Cao, Yuan; Suykens, Johan A. K.
Published in: Internal report, 2024
Publisher: KU Leuven
DOI: 10.48550/arxiv.2401.13624

Indefinite Kernel Logistic Regression With Concave-Inexact-Convex Procedure

Author(s): Fanghui Liu; Xiaolin Huang; Chen Gong; Jie Yang; Johan A. K. Suykens
Published in: IEEE Transactions on Neural Networks and Learning Systems, 2019, ISSN 3004-7906
Publisher: IEEE
DOI: 10.1109/tnnls.2018.2851305

Enhancing Kernel Flexibility via Learning Asymmetric Locally-Adaptive Kernels

Author(s): Fan He, Mingzhen He, Lei Shi, Xiaolin Huang, Johan A.K. Suykens
Published in: Internal Report, 2023
Publisher: KU Leuven
DOI: 10.48550/arxiv.2310.05236

Nonlinear SVD with Asymmetric Kernels: feature learning and asymmetric Nyström method

Author(s): Tao, Qinghua; Tonin, Francesco; Patrinos, Panagiotis; Suykens, Johan A. K.
Published in: Internal Report, 2023
Publisher: KU Leuven
DOI: 10.48550/arxiv.2306.07040

Functional Output Regression with Infimal Convolution: Exploring the Huber and $ε$-insensitive Losses

Author(s): Lambert, Alex; Bouche, Dimitri; Szabo, Zoltan; d'Alché-Buc, Florence
Published in: https://hal.science/hal-03807108, Issue 1, 2022
Publisher: KU Leuven
DOI: 10.48550/arxiv.2206.08220

Nonlinear functional regression by functional deep neural network with kernel embedding

Author(s): Shi, Zhongjie; Fan, Jun; Song, Linhao; Zhou, Ding-Xuan; Suykens, Johan A. K.
Published in: Internal report, Issue 2, 2024
Publisher: KU Leuven
DOI: 10.48550/arxiv.2401.02890

A flexible alarm prediction system for smart manufacturing scenarios following a forecaster–analyzer approach

Author(s): Kevin Villalobos, Johan Suykens, Arantza Illarramendi
Published in: Journal of Intelligent Manufacturing, Issue 32/5, 2021, Page(s) 1323-1344, ISSN 0956-5515
Publisher: Kluwer Academic Publishers
DOI: 10.1007/s10845-020-01614-w

Multi-view Kernel PCA for Time series Forecasting

Author(s): Pandey, A; De Meulemeester, H; De Moor, Bart; Suykens, J
Published in: Neurocomputing, Issue 2023; Vol. 554, 2023, ISSN 0925-2312
Publisher: Elsevier BV
DOI: 10.1016/j.neucom.2023.126639

Transfer Learning in Demand Response: a Review of Algorithms for Data-efficient Modelling and Control

Author(s): Peirelinck, Thijs; Kazmi, Hussain Syed; Mbuwir, Brida; Hermans, Chris; Spiessens, Fred; Suykens, Johan; Deconinck, Geert
Published in: Energy and AI, Issue 2022; Vol. 7, 2022, ISSN 2666-5468
Publisher: Elsevier
DOI: 10.1016/j.egyai.2021.100126

Toward Deep Adaptive Hinging Hyperplanes

Author(s): Qinghua Tao, Jun Xu, Zhen Li, Na Xie, Shuning Wang, Xiaoli Li, Johan A. K. Suykens
Published in: IEEE Transactions on Neural Networks and Learning Systems, 2021, Page(s) 1-15, ISSN 2162-237X
Publisher: IEEE Computational Intelligence Society
DOI: 10.1109/tnnls.2021.3079113

Jigsaw-ViT: Learning Jigsaw Puzzles in Vision Transformer

Author(s): Chen, Y; Shen, X; Liu, Y; Tao, Q; Suykens, Johan
Published in: Pattern Recognition Letters, 2023, ISSN 0167-8655
Publisher: Elsevier BV
DOI: 10.1016/j.patrec.2022.12.023

Random Features for Kernel Approximation: A Survey on Algorithms, Theory, and Beyond

Author(s): Fanghui Liu, Xiaolin Huang, Yudong Chen, Johan A. K. Suykens
Published in: IEEE Transactions on Pattern Analysis and Machine Intelligence, 2020, Page(s) 1-1, ISSN 0162-8828
Publisher: Institute of Electrical and Electronics Engineers
DOI: 10.1109/tpami.2021.3097011

Explainable deep convolutional learning for intuitive model development by non–machine learning domain experts

Author(s): Sundaravelpandian Singaravel, Johan Suykens, Hans Janssen, Philipp Geyer
Published in: Design Science, Issue 6, 2020, ISSN 2053-4701
Publisher: DSJ
DOI: 10.1017/dsj.2020.22

Positive semi-definite embedding for dimensionality reduction andout-of-sample extensions

Author(s): Fanuel M., Aspeel A., Delvenne J.C., Suykens J.A.K.,
Published in: SIAM Journal on Mathematics of Data Science, Issue Article accepted for publication, 2021, ISSN 2577-0187
Publisher: Society for Industrial and Applied Mathematics
DOI: 10.1137/20m1370653

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

Author(s): Theodorakos, Konstantinos; Agudelo Manozca, Oscar; Schreurs, J; Suykens, J; De Moor, Bart
Published in: Ieee Transactions On Evolutionary Computation, 2023, ISSN 1089-778X
Publisher: Institute of Electrical and Electronics Engineers
DOI: 10.1109/tevc.2022.3189500

Nyström landmark sampling and regularized Christoffel functions

Author(s): Michaël Fanuel; Joachim Schreurs; Johan A. K. Suykens
Published in: Machine Learning;, Issue 2022; Vol. 111; iss. 6, 2022, Page(s) 2213 - 2254, ISSN 0885-6125
Publisher: Kluwer Academic Publishers
DOI: 10.1007/s10994-022-06165-0

Generalization Properties of hyper-RKHS and its Applications

Author(s): Liu, Fanghui ; Shi, Lei ; Huang, Xiaolin ; Yang, Jie ; Suykens, Johan AK
Published in: Journal Of Machine Learning Research; 2021; Vol. 22; pp. -, 2021, ISSN 1532-4435
Publisher: MIT Press

Towards a Unified Quadrature Framework for Large-Scale Kernel Machines

Author(s): Fanghui Liu, Xiaolin Huang, Yudong Chen, Johan A. K. Suykens
Published in: IEEE Transactions on Pattern Analysis and Machine Intelligence, 2021, Page(s) 1-1, ISSN 0162-8828
Publisher: Institute of Electrical and Electronics Engineers
DOI: 10.1109/tpami.2021.3120183

Analysis of regularized least-squares in reproducing kernel Kreĭn spaces

Author(s): Fanghui Liu, Lei Shi, Xiaolin Huang, Jie Yang, Johan A. K. Suykens
Published in: Machine Learning, 2021, ISSN 0885-6125
Publisher: Kluwer Academic Publishers
DOI: 10.1007/s10994-021-05955-2

Generative Restricted Kernel Machines: A framework for multi-view generation and disentangled feature learning

Author(s): Arun Pandey, Joachim Schreurs, Johan A.K. Suykens
Published in: Neural Networks, Issue 135, 2021, Page(s) 177-191, ISSN 0893-6080
Publisher: Pergamon Press Ltd.
DOI: 10.1016/j.neunet.2020.12.010

Denoising modulo samples: k-NN regression and tightness of SDP relaxation

Author(s): Fanuel, Michaël; Tyagi, Hemant
Published in: Information and Inference, Oxford University Press (OUP), 2021, Issue 4, 2021, ISSN 2049-8772
Publisher: Institute of Mathematics and its Applications
DOI: 10.1093/imaiai/iaab022

Learning with continuous piecewise linear decision trees

Author(s): Qinghua Tao, Zhen Li, Jun Xu, Na Xie, Shuning Wang, Johan A.K. Suykens
Published in: Expert Systems with Applications, Issue 168, 2021, Page(s) 114214, ISSN 0957-4174
Publisher: Pergamon Press Ltd.
DOI: 10.1016/j.eswa.2020.114214

A Double-Variational Bayesian Framework in Random Fourier Features for Indefinite Kernels

Author(s): Fanghui Liu, Xiaolin Huang, Lei Shi, Jie Yang, Johan A. K. Suykens
Published in: IEEE Transactions on Neural Networks and Learning Systems, Issue 31/8, 2020, Page(s) 2965-2979, ISSN 2162-237X
Publisher: IEEE Computational Intelligence Society
DOI: 10.1109/tnnls.2019.2934729

Random Fourier Features via Fast Surrogate Leverage Weighted Sampling

Author(s): Fanghui Liu, Xiaolin Huang, Yudong Chen, Jie Yang, Johan Suykens
Published in: Proceedings of the AAAI Conference on Artificial Intelligence, Issue 34/04, 2020, Page(s) 4844-4851, ISSN 2374-3468
Publisher: AAAI Press
DOI: 10.1609/aaai.v34i04.5920

Outlier detection in non-elliptical data by kernel MRCD

Author(s): Joachim Schreurs, Iwein Vranckx, Mia Hubert, Johan A. K. Suykens, Peter J. Rousseeuw
Published in: Statistics and Computing, Issue 31/5, 2021, ISSN 0960-3174
Publisher: Kluwer Academic Publishers
DOI: 10.1007/s11222-021-10041-7

Unsupervised learning of disentangled representations in deep restricted kernel machines with orthogonality constraints

Author(s): Francesco Tonin, Panagiotis Patrinos, Johan A.K. Suykens
Published in: Neural Networks, Issue 142, 2021, Page(s) 661-679, ISSN 0893-6080
Publisher: Pergamon Press Ltd.
DOI: 10.1016/j.neunet.2021.07.023

Generalized support vector regression: Duality and tensor-kernel representation

Author(s): Saverio Salzo, Johan A. K. Suykens
Published in: Analysis and Applications, Issue 18/01, 2020, Page(s) 149-183, ISSN 0219-5305
Publisher: World Scientific
DOI: 10.1142/s0219530519410069

Deformed Laplacians and spectral ranking in directed networks

Author(s): M. Fanuel, J.A.K. Suykens
Published in: Applied and Computational Harmonic Analysis, Issue 47/2, 2019, Page(s) 397-422, ISSN 1063-5203
Publisher: Academic Press
DOI: 10.1016/j.acha.2017.09.002

Sparse Kernel Regression with Coefficient-based ℓq− regularization

Author(s): Lei Shi, Xiaolin Huang, Yunlong Feng, Johan A.K. Suykens
Published in: Journal of Machine Learning Research, Issue 20(161), 2019, Page(s) 1-44, ISSN 1532-4435
Publisher: MIT Press

Robust classification of graph-based data

Author(s): Carlos M. Alaíz, Michaël Fanuel, Johan A. K. Suykens
Published in: Data Mining and Knowledge Discovery, Issue 33/1, 2019, Page(s) 230-251, ISSN 1384-5810
Publisher: Kluwer Academic Publishers
DOI: 10.1007/s10618-018-0603-9

Multi-View Kernel Spectral Clustering

Author(s): Lynn Houthuys, Rocco Langone, Johan A.K. Suykens
Published in: Information Fusion, Issue 44, 2018, Page(s) 46-56, ISSN 1566-2535
Publisher: Elsevier BV
DOI: 10.1016/j.inffus.2017.12.002

Parallelized Tensor Train Learning of Polynomial Classifiers

Author(s): Zhongming Chen, Kim Batselier, Johan A. K. Suykens, Ngai Wong
Published in: IEEE Transactions on Neural Networks and Learning Systems, Issue 29/10, 2018, Page(s) 4621-4632, ISSN 2162-237X
Publisher: IEEE Computational Intelligence Society
DOI: 10.1109/tnnls.2017.2771264

A Statistical Learning Approach to Modal Regression

Author(s): Yunlong Feng, Jun Fan, Johan A.K. Suykens
Published in: Journal of Machine Learning Research, Issue 21(2), 2020, Page(s) 1-35, ISSN 1532-4435
Publisher: MIT Press

Modified Frank–Wolfe algorithm for enhanced sparsity in support vector machine classifiers

Author(s): Carlos M. Alaíz, Johan A.K. Suykens
Published in: Neurocomputing, Issue 320, 2018, Page(s) 47-59, ISSN 0925-2312
Publisher: Elsevier BV
DOI: 10.1016/j.neucom.2018.08.049

Transductive LSTM for time-series prediction: An application to weather forecasting

Author(s): Zahra Karevan, Johan A.K. Suykens
Published in: Neural Networks, Issue 125, 2020, Page(s) 1-9, ISSN 0893-6080
Publisher: Pergamon Press Ltd.
DOI: 10.1016/j.neunet.2019.12.030

Deep convolutional learning for general early design stage prediction models

Author(s): Sundaravelpandian Singaravel, Johan Suykens, Philipp Geyer
Published in: Advanced Engineering Informatics, Issue 42, 2019, Page(s) 100982, ISSN 1474-0346
Publisher: Pergamon Press Ltd.
DOI: 10.1016/j.aei.2019.100982

Disentangled Representation Learning and Generation With Manifold Optimization

Author(s): Arun, Pandey; Michaël, Fanuel; Joachim, Schreurs; Johan A K, Suykens
Published in: Neural Computation, Issue Vol. 34; iss. 10; pp. 2009 - 2036, 2022, ISSN 0899-7667
Publisher: MIT Press
DOI: 10.1162/neco_a_01528

Diversity Sampling is an Implicit Regularization for Kernel Methods

Author(s): Michael Fanuel, Joachim Schreurs, Johan Suykens
Published in: SIAM Journal on Mathematics of Data Science, Issue 3/1, 2021, Page(s) 280-297, ISSN 2577-0187
Publisher: SIAM
DOI: 10.1137/20m1320031

A novel neural grey system model with Bayesian regularization and its applications

Author(s): Xin Ma; Mei Xie; Johan A.K. Suykens
Published in: Elsevier Neurocomputing, Issue 2, 2021, ISSN 0925-2312
Publisher: Elsevier BV
DOI: 10.1016/j.neucom.2021.05.048

Determinantal Point Processes Implicitly Regularize Semiparametric Regression Problems

Author(s): Michaël Fanuel; Joachim Schreurs; Johan A. K. Suykens
Published in: SIAM journal on Mathematics of Data Science, Issue 1, 2022, ISSN 2577-0187
Publisher: SIAM
DOI: 10.1137/21m1403977

Piecewise Linear Neural Networks and Deep Learning

Author(s): Tao, Q; Li, L; Huang, X; Wang, S; Suykens, Johan
Published in: Nature Reviews Methods Primers, Issue 2022; Vol. 2; iss 1, 2022, ISSN 2662-8449
Publisher: Nature
DOI: 10.1038/s43586-022-00125-7

Compressing Features for Learning with Noisy Labels

Author(s): Yingyi Chen; Shell Xu Hu; Xi Shen; Chunrong Ai; Johan A. K. Suykens
Published in: Crossref, Issue 5, 2022, ISSN 2162-237X
Publisher: IEEE Computational Intelligence Society
DOI: 10.48550/arxiv.2206.13140

Determinantal Point Processes Implicitly Regularize Semi-parametric Regression Problems

Author(s): Michaël Fanuel, Joachim Schreurs, Johan A.K. Suykens
Published in: SIAM journal on Mathematics of Data Science, Issue 4 (3), 1171-1190, 2022, ISSN 2577-0187
Publisher: SIAM
DOI: 10.48550/arxiv.2011.06964

Learning with asymmetric kernels : Least squares and feature interpretation

Author(s): He, M; He, F; Shi, L; Huang, X; Suykens, Johan
Published in: Ieee Transactions On Pattern Analysis And Machine Intelligence, 2023, ISSN 0162-8828
Publisher: Institute of Electrical and Electronics Engineers
DOI: 10.1109/tpami.2023.3257351

Short-Term Traffic Flow Prediction Based on the Efficient Hinging Hyperplanes Neural Network

Author(s): Tao, Qinghua; Li, Z; Xu, J; Lin, S; De Schutter, Bart; Suykens, J
Published in: Ieee Transactions On Intelligent Transportation Systems; 2022, Issue Vol. 23; iss. 9, 2022, ISSN 1524-9050
Publisher: Institute of Electrical and Electronics Engineers
DOI: 10.1109/tits.2022.3142728

Deep kernel principal component analysis for multi-level feature learning

Author(s): Tonin, F; Tao, Q; Patrinos, Panagiotis; Suykens, J
Published in: Neural Networks, Issue 2024; Vol. 170; pp. 578 - 595, 2024, ISSN 0893-6080
Publisher: Pergamon Press Ltd.
DOI: 10.1016/j.neunet.2023.11.045

Efficient hinging hyperplanes neural network and its application in nonlinear system identification

Author(s): Jun Xu, Qinghua Tao, Zhen Li, Xiangming Xi, Johan A.K. Suykens, Shuning Wang
Published in: Automatica, Issue 116, 2020, Page(s) 108906, ISSN 0005-1098
Publisher: Pergamon Press Ltd.
DOI: 10.1016/j.automatica.2020.108906

Tensor-based restricted kernel machines for multi-view classification

Author(s): Lynn Houthuys, Johan A.K. Suykens
Published in: Information Fusion, Issue 68, 2021, Page(s) 54-66, ISSN 1566-2535
Publisher: Elsevier BV
DOI: 10.1016/j.inffus.2020.10.022

Tensor-based multi-view spectral clustering via shared latent space

Author(s): Tao, Q; Tonin, F; Patrinos, P; Suykens, Johan
Published in: Information Fusion; 2024; Vol. 108, 2024, ISSN 1566-2535
Publisher: Elsevier BV
DOI: 10.1016/j.inffus.2024.102405

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