Exploring Duality for Future Data-driven Modelling

Duality in Multi-View Restricted Kernel Machines

Autorzy: Achten, Sonny; Pandey, Arun; De Meulemeester, Hannes; De Moor, Bart; Suykens, Johan A. K.
Opublikowane w: ICML Workshop on Duality for Modern Machine Learning,, Numer 5, 2023
Wydawca: ICML
DOI: 10.48550/arxiv.2305.17251

A Dual Formulation for Probabilistic Principal Component Analysis

Autorzy: De Plaen, Henri; Suykens, J
Opublikowane w: Proceedings ol ICML 2023 Workshop on Duality Principles for Modern Machine Learning (DP4ML);, Numer 1, 2023
Wydawca: DP4ML
DOI: 10.48550/arxiv.2307.10078

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

Autorzy: Tonin, Francesco; Pandey, Arun; Patrinos, Panagiotis; Suykens, Johan A. K.
Opublikowane w: International Joint Conference on Neural Networks, Numer 4, 2021, ISSN 2161-4393
Wydawca: Institute of Electrical and Electronics Engineers
DOI: 10.1109/ijcnn52387.2021.9533706

A Theoretical Framework for Target Propagation

Autorzy: Meulemans, Alexander; Carzaniga, Francesco; Suykens, Johan A.K.; Sacramento, João; Grewe, Benjamin F.
Opublikowane w: Advances in Neural Information Processing Systems, Numer 33, 2020, Strona(/y) 20024--20036
Wydawca: NeurIPS
DOI: 10.5167/uzh-198834

Recurrent Restricted Kernel Machines for Time-series Forecasting

Autorzy: Pandey, A; De Meulemeester, H; De Plaen, H; De Moor, B; Suykens, Johan
Opublikowane w: European symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, Numer ESANN 2022, 2022
Wydawca: ESANN

Boosting Co-teaching with Compression Regularization for Label Noise

Autorzy: Yingyi Chen, Xi Shen, Shell Xu Hu, Johan A. K. Suykens
Opublikowane w: 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), 2021, Strona(/y) 2682-2686, ISBN 978-1-6654-4899-4
Wydawca: IEEE
DOI: 10.1109/cvprw53098.2021.00302

Unsupervised Neighborhood Propagation Kernel Layers for Semi-supervised Node Classification

Autorzy: Achten, Sonny; Tonin, F; Patrinos, Panagiotis; Suykens, J
Opublikowane w: AAAI Conference on Artificial Intelligence, Numer 2024, 2024, ISBN 1-57735-887-2
Wydawca: AAAI Press
DOI: 10.1609/aaai.v38i10.28949

The Bures Metric for Generative Adversarial Networks

Autorzy: De Meulemeester, Hannes; Schreurs, Joachim; Fanuel, Michaël; De Moor, Bart; Suykens, Johan A. K.
Opublikowane w: The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, 2021
Wydawca: ECML-PKDD 2021

Ensemble Kernel Methods, Implicit Regularization and Determinantal Point Processes

Autorzy: Schreurs, Joachim; Fanuel, M; Suykens, J
Opublikowane w: ICML 2020 Workshop on Negative Dependence and Submodularity for ML, Numer 15, 2020
Wydawca: ICML

Wasserstein Exponential Kernels

Autorzy: Henri De Plaen, Michael Fanuel, Johan A. K. Suykens
Opublikowane w: 2020 International Joint Conference on Neural Networks (IJCNN), 2020, Strona(/y) 1-6, ISBN 978-1-7281-6926-2
Wydawca: IEEE
DOI: 10.1109/ijcnn48605.2020.9207630

Leverage Score Sampling for Complete Mode Coverage in Generative Adversarial Networks

Autorzy: Schreurs J., De Meulemeester H., Fanuel M., De Moor B., Suykens J.A.K
Opublikowane w: Conference on Machine Learning, Optimization and Data Science, 2021, ISBN 978-3-030-95469-7
Wydawca: Springer
DOI: 10.1007/978-3-030-95470-3_35

Fast Adaptive Hinging Hyperplanes

Autorzy: Qinghua Tao, Jun Xu, Johan A.K. Suykens, Shuning Wang
Opublikowane w: 2018 IEEE Conference on Decision and Control (CDC), 2018, Strona(/y) 1482-1487, ISBN 978-1-5386-1395-5
Wydawca: IEEE
DOI: 10.1109/cdc.2018.8619653

Fast Learning in Reproducing Kernel Krein Spaces via Signed Measures

Autorzy: Fanghui Liu, Xiaolin Huang, Yingyi Chen, Johan Suykens
Opublikowane w: roceedings of The 24th International Conference on Artificial Intelligence and Statistics, Numer PMLR 130, 2021, Strona(/y) 388-396
Wydawca: PMLR

Kernel regression in high dimensions: Refined analysis beyond double descent

Autorzy: Fanghui Liu, Zhenyu Liao, Johan Suykens
Opublikowane w: Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, Numer PMLR 130, 2021, Strona(/y) 649-657
Wydawca: PMLR

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

Autorzy: Chen, Yingyi; Tao, Qinghua; Tonin, Francesco; Suykens, Johan A. K.
Opublikowane w: Proc. of NeurIPS 2023, Numer 1, 2023
Wydawca: NeuriPS
DOI: 10.48550/arxiv.2305.19798

Unbalanced Optimal Transport: A Unified Framework for Object Detection

Autorzy: De Plaen, Henri; De Plaen, P; Suykens, J; Proesmans, M; Tuytelaars, T; Van Gool, L
Opublikowane w: Proceedings / CVPR, IEEE Computer Society Conference on Computer Vision and Pattern, Numer 5, 2023, ISSN 1063-6919
Wydawca: IEEE
DOI: 10.1109/cvpr52729.2023.00312

The Bures Metric for Generative Adversarial Networks

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

Latent Space Exploration Using Generative Kernel PCA

Autorzy: David Winant, Joachim Schreurs, Johan A. K. Suykens
Opublikowane w: 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, Numer 1196, 2020, Strona(/y) 70-82, ISBN 978-3-030-65153-4
Wydawca: Springer International Publishing
DOI: 10.1007/978-3-030-65154-1_5

Robust Generative Restricted Kernel Machines Using Weighted Conjugate Feature Duality

Autorzy: Arun Pandey, Joachim Schreurs, Johan A. K. Suykens
Opublikowane w: Machine Learning, Optimization, and Data Science - 6th International Conference, LOD 2020, Siena, Italy, July 19–23, 2020, Revised Selected Papers, Part I, Numer 12565, 2020, Strona(/y) 613-624, ISBN 978-3-030-64582-3
Wydawca: Springer International Publishing
DOI: 10.1007/978-3-030-64583-0_54

Towards Deterministic Diverse Subset Sampling

Autorzy: J. Schreurs, M. Fanuel, J. A. K. Suykens
Opublikowane w: 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, Numer 1196, 2020, Strona(/y) 137-151, ISBN 978-3-030-65153-4
Wydawca: Springer International Publishing
DOI: 10.1007/978-3-030-65154-1_8

Fast Hyperparameter Tuning for Support Vector Machines with Stochastic Gradient Descent

Autorzy: Marcin Orchel, Johan A. K. Suykens
Opublikowane w: Machine Learning, Optimization, and Data Science - 6th International Conference, LOD 2020, Siena, Italy, July 19–23, 2020, Revised Selected Papers, Part II, Numer 12566, 2020, Strona(/y) 481-493, ISBN 978-3-030-64579-3
Wydawca: Springer International Publishing
DOI: 10.1007/978-3-030-64580-9_40

Tensor Learning in Multi-view Kernel PCA

Autorzy: Lynn Houthuys, Johan A. K. Suykens
Opublikowane w: Artificial Neural Networks and Machine Learning – ICANN 2018 - 27th International Conference on Artificial Neural Networks, Rhodes, Greece, October 4-7, 2018, Proceedings, Part II, Numer 11140, 2018, Strona(/y) 205-215, ISBN 978-3-030-01420-9
Wydawca: Springer International Publishing
DOI: 10.1007/978-3-030-01421-6_21

Weighted Multi-view Deep Neural Networks for Weather Forecasting

Autorzy: Zahra Karevan, Lynn Houthuys, Johan A. K. Suykens
Opublikowane w: Artificial Neural Networks and Machine Learning – ICANN 2018 - 27th International Conference on Artificial Neural Networks, Rhodes, Greece, October 4-7, 2018, Proceedings, Part III, Numer 11141, 2018, Strona(/y) 489-499, ISBN 978-3-030-01423-0
Wydawca: Springer International Publishing
DOI: 10.1007/978-3-030-01424-7_48

Axiomatic Kernels on Graphs for Support Vector Machines

Autorzy: Marcin Orchel, Johan A. K. Suykens
Opublikowane w: 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, Numer 11731, 2019, Strona(/y) 685-700, ISBN 978-3-030-30492-8
Wydawca: Springer International Publishing
DOI: 10.1007/978-3-030-30493-5_62

Low-Rank Multitask Learning based on Tensorized SVMs and LSSVMs

Autorzy: Liu, Jiani; Tao, Qinghua; Zhu, Ce; Liu, Yipeng; Huang, Xiaolin; Suykens, Johan A. K.
Opublikowane w: Technical report, Numer 1, 2023
Wydawca: KU Leuven
DOI: 10.48550/arxiv.2308.16056

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

Autorzy: Lambert, Alex; Bouche, Dimitri; Szabo, Zoltan; d'Alché-Buc, Florence
Opublikowane w: https://hal.science/hal-03807108, Numer 1, 2022
Wydawca: KU Leuven
DOI: 10.48550/arxiv.2206.08220

Nonlinear functional regression by functional deep neural network with kernel embedding

Autorzy: Shi, Zhongjie; Fan, Jun; Song, Linhao; Zhou, Ding-Xuan; Suykens, Johan A. K.
Opublikowane w: Internal report, Numer 2, 2024
Wydawca: KU Leuven
DOI: 10.48550/arxiv.2401.02890

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

Autorzy: Kevin Villalobos, Johan Suykens, Arantza Illarramendi
Opublikowane w: Journal of Intelligent Manufacturing, Numer 32/5, 2021, Strona(/y) 1323-1344, ISSN 0956-5515
Wydawca: Kluwer Academic Publishers
DOI: 10.1007/s10845-020-01614-w

Multi-view Kernel PCA for Time series Forecasting

Autorzy: Pandey, A; De Meulemeester, H; De Moor, Bart; Suykens, J
Opublikowane w: Neurocomputing, Numer 2023; Vol. 554, 2023, ISSN 0925-2312
Wydawca: Elsevier BV
DOI: 10.1016/j.neucom.2023.126639

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

Autorzy: Peirelinck, Thijs; Kazmi, Hussain Syed; Mbuwir, Brida; Hermans, Chris; Spiessens, Fred; Suykens, Johan; Deconinck, Geert
Opublikowane w: Energy and AI, Numer 2022; Vol. 7, 2022, ISSN 2666-5468
Wydawca: Elsevier
DOI: 10.1016/j.egyai.2021.100126

Toward Deep Adaptive Hinging Hyperplanes

Autorzy: Qinghua Tao, Jun Xu, Zhen Li, Na Xie, Shuning Wang, Xiaoli Li, Johan A. K. Suykens
Opublikowane w: IEEE Transactions on Neural Networks and Learning Systems, 2021, Strona(/y) 1-15, ISSN 2162-237X
Wydawca: IEEE Computational Intelligence Society
DOI: 10.1109/tnnls.2021.3079113

Jigsaw-ViT: Learning Jigsaw Puzzles in Vision Transformer

Autorzy: Chen, Y; Shen, X; Liu, Y; Tao, Q; Suykens, Johan
Opublikowane w: Pattern Recognition Letters, 2023, ISSN 0167-8655
Wydawca: Elsevier BV
DOI: 10.1016/j.patrec.2022.12.023

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

Autorzy: Fanghui Liu, Xiaolin Huang, Yudong Chen, Johan A. K. Suykens
Opublikowane w: IEEE Transactions on Pattern Analysis and Machine Intelligence, 2020, Strona(/y) 1-1, ISSN 0162-8828
Wydawca: 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

Autorzy: Sundaravelpandian Singaravel, Johan Suykens, Hans Janssen, Philipp Geyer
Opublikowane w: Design Science, Numer 6, 2020, ISSN 2053-4701
Wydawca: DSJ
DOI: 10.1017/dsj.2020.22

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

Autorzy: Fanuel M., Aspeel A., Delvenne J.C., Suykens J.A.K.,
Opublikowane w: SIAM Journal on Mathematics of Data Science, Numer Article accepted for publication, 2021, ISSN 2577-0187
Wydawca: Society for Industrial and Applied Mathematics
DOI: 10.1137/20m1370653

Nyström landmark sampling and regularized Christoffel functions

Autorzy: Michaël Fanuel; Joachim Schreurs; Johan A. K. Suykens
Opublikowane w: Machine Learning;, Numer 2022; Vol. 111; iss. 6, 2022, Strona(/y) 2213 - 2254, ISSN 0885-6125
Wydawca: Kluwer Academic Publishers
DOI: 10.1007/s10994-022-06165-0

Towards a Unified Quadrature Framework for Large-Scale Kernel Machines

Autorzy: Fanghui Liu, Xiaolin Huang, Yudong Chen, Johan A. K. Suykens
Opublikowane w: IEEE Transactions on Pattern Analysis and Machine Intelligence, 2021, Strona(/y) 1-1, ISSN 0162-8828
Wydawca: Institute of Electrical and Electronics Engineers
DOI: 10.1109/tpami.2021.3120183

Analysis of regularized least-squares in reproducing kernel Kreĭn spaces

Autorzy: Fanghui Liu, Lei Shi, Xiaolin Huang, Jie Yang, Johan A. K. Suykens
Opublikowane w: Machine Learning, 2021, ISSN 0885-6125
Wydawca: Kluwer Academic Publishers
DOI: 10.1007/s10994-021-05955-2

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

Autorzy: Arun Pandey, Joachim Schreurs, Johan A.K. Suykens
Opublikowane w: Neural Networks, Numer 135, 2021, Strona(/y) 177-191, ISSN 0893-6080
Wydawca: Pergamon Press Ltd.
DOI: 10.1016/j.neunet.2020.12.010

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

Autorzy: Fanuel, Michaël; Tyagi, Hemant
Opublikowane w: Information and Inference, Oxford University Press (OUP), 2021, Numer 4, 2021, ISSN 2049-8772
Wydawca: Institute of Mathematics and its Applications
DOI: 10.1093/imaiai/iaab022

Learning with continuous piecewise linear decision trees

Autorzy: Qinghua Tao, Zhen Li, Jun Xu, Na Xie, Shuning Wang, Johan A.K. Suykens
Opublikowane w: Expert Systems with Applications, Numer 168, 2021, Strona(/y) 114214, ISSN 0957-4174
Wydawca: Pergamon Press Ltd.
DOI: 10.1016/j.eswa.2020.114214

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

Autorzy: Fanghui Liu, Xiaolin Huang, Lei Shi, Jie Yang, Johan A. K. Suykens
Opublikowane w: IEEE Transactions on Neural Networks and Learning Systems, Numer 31/8, 2020, Strona(/y) 2965-2979, ISSN 2162-237X
Wydawca: IEEE Computational Intelligence Society
DOI: 10.1109/tnnls.2019.2934729

Random Fourier Features via Fast Surrogate Leverage Weighted Sampling

Autorzy: Fanghui Liu, Xiaolin Huang, Yudong Chen, Jie Yang, Johan Suykens
Opublikowane w: Proceedings of the AAAI Conference on Artificial Intelligence, Numer 34/04, 2020, Strona(/y) 4844-4851, ISSN 2374-3468
Wydawca: AAAI Press
DOI: 10.1609/aaai.v34i04.5920

Outlier detection in non-elliptical data by kernel MRCD

Autorzy: Joachim Schreurs, Iwein Vranckx, Mia Hubert, Johan A. K. Suykens, Peter J. Rousseeuw
Opublikowane w: Statistics and Computing, Numer 31/5, 2021, ISSN 0960-3174
Wydawca: Kluwer Academic Publishers
DOI: 10.1007/s11222-021-10041-7

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

Autorzy: Francesco Tonin, Panagiotis Patrinos, Johan A.K. Suykens
Opublikowane w: Neural Networks, Numer 142, 2021, Strona(/y) 661-679, ISSN 0893-6080
Wydawca: Pergamon Press Ltd.
DOI: 10.1016/j.neunet.2021.07.023

Generalized support vector regression: Duality and tensor-kernel representation

Autorzy: Saverio Salzo, Johan A. K. Suykens
Opublikowane w: Analysis and Applications, Numer 18/01, 2020, Strona(/y) 149-183, ISSN 0219-5305
Wydawca: World Scientific
DOI: 10.1142/s0219530519410069

Deformed Laplacians and spectral ranking in directed networks

Autorzy: M. Fanuel, J.A.K. Suykens
Opublikowane w: Applied and Computational Harmonic Analysis, Numer 47/2, 2019, Strona(/y) 397-422, ISSN 1063-5203
Wydawca: Academic Press
DOI: 10.1016/j.acha.2017.09.002

Sparse Kernel Regression with Coefficient-based ℓq− regularization

Autorzy: Lei Shi, Xiaolin Huang, Yunlong Feng, Johan A.K. Suykens
Opublikowane w: Journal of Machine Learning Research, Numer 20(161), 2019, Strona(/y) 1-44, ISSN 1532-4435
Wydawca: MIT Press

Robust classification of graph-based data

Autorzy: Carlos M. Alaíz, Michaël Fanuel, Johan A. K. Suykens
Opublikowane w: Data Mining and Knowledge Discovery, Numer 33/1, 2019, Strona(/y) 230-251, ISSN 1384-5810
Wydawca: Kluwer Academic Publishers
DOI: 10.1007/s10618-018-0603-9

Multi-View Kernel Spectral Clustering

Autorzy: Lynn Houthuys, Rocco Langone, Johan A.K. Suykens
Opublikowane w: Information Fusion, Numer 44, 2018, Strona(/y) 46-56, ISSN 1566-2535
Wydawca: Elsevier BV
DOI: 10.1016/j.inffus.2017.12.002

Parallelized Tensor Train Learning of Polynomial Classifiers

Autorzy: Zhongming Chen, Kim Batselier, Johan A. K. Suykens, Ngai Wong
Opublikowane w: IEEE Transactions on Neural Networks and Learning Systems, Numer 29/10, 2018, Strona(/y) 4621-4632, ISSN 2162-237X
Wydawca: IEEE Computational Intelligence Society
DOI: 10.1109/tnnls.2017.2771264

A Statistical Learning Approach to Modal Regression

Autorzy: Yunlong Feng, Jun Fan, Johan A.K. Suykens
Opublikowane w: Journal of Machine Learning Research, Numer 21(2), 2020, Strona(/y) 1-35, ISSN 1532-4435
Wydawca: MIT Press

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

Autorzy: Carlos M. Alaíz, Johan A.K. Suykens
Opublikowane w: Neurocomputing, Numer 320, 2018, Strona(/y) 47-59, ISSN 0925-2312
Wydawca: Elsevier BV
DOI: 10.1016/j.neucom.2018.08.049

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

Autorzy: Zahra Karevan, Johan A.K. Suykens
Opublikowane w: Neural Networks, Numer 125, 2020, Strona(/y) 1-9, ISSN 0893-6080
Wydawca: Pergamon Press Ltd.
DOI: 10.1016/j.neunet.2019.12.030

Deep convolutional learning for general early design stage prediction models

Autorzy: Sundaravelpandian Singaravel, Johan Suykens, Philipp Geyer
Opublikowane w: Advanced Engineering Informatics, Numer 42, 2019, Strona(/y) 100982, ISSN 1474-0346
Wydawca: Pergamon Press Ltd.
DOI: 10.1016/j.aei.2019.100982

Disentangled Representation Learning and Generation With Manifold Optimization

Autorzy: Arun, Pandey; Michaël, Fanuel; Joachim, Schreurs; Johan A K, Suykens
Opublikowane w: Neural Computation, Numer Vol. 34; iss. 10; pp. 2009 - 2036, 2022, ISSN 0899-7667
Wydawca: MIT Press
DOI: 10.1162/neco_a_01528

Diversity Sampling is an Implicit Regularization for Kernel Methods

Autorzy: Michael Fanuel, Joachim Schreurs, Johan Suykens
Opublikowane w: SIAM Journal on Mathematics of Data Science, Numer 3/1, 2021, Strona(/y) 280-297, ISSN 2577-0187
Wydawca: SIAM
DOI: 10.1137/20m1320031

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

Autorzy: Xin Ma; Mei Xie; Johan A.K. Suykens
Opublikowane w: Elsevier Neurocomputing, Numer 2, 2021, ISSN 0925-2312
Wydawca: Elsevier BV
DOI: 10.1016/j.neucom.2021.05.048

Determinantal Point Processes Implicitly Regularize Semiparametric Regression Problems

Autorzy: Michaël Fanuel; Joachim Schreurs; Johan A. K. Suykens
Opublikowane w: SIAM journal on Mathematics of Data Science, Numer 1, 2022, ISSN 2577-0187
Wydawca: SIAM
DOI: 10.1137/21m1403977

Piecewise Linear Neural Networks and Deep Learning

Autorzy: Tao, Q; Li, L; Huang, X; Wang, S; Suykens, Johan
Opublikowane w: Nature Reviews Methods Primers, Numer 2022; Vol. 2; iss 1, 2022, ISSN 2662-8449
Wydawca: Nature
DOI: 10.1038/s43586-022-00125-7

Compressing Features for Learning with Noisy Labels

Autorzy: Yingyi Chen; Shell Xu Hu; Xi Shen; Chunrong Ai; Johan A. K. Suykens
Opublikowane w: Crossref, Numer 5, 2022, ISSN 2162-237X
Wydawca: IEEE Computational Intelligence Society
DOI: 10.48550/arxiv.2206.13140

Determinantal Point Processes Implicitly Regularize Semi-parametric Regression Problems

Autorzy: Michaël Fanuel, Joachim Schreurs, Johan A.K. Suykens
Opublikowane w: SIAM journal on Mathematics of Data Science, Numer 4 (3), 1171-1190, 2022, ISSN 2577-0187
Wydawca: SIAM
DOI: 10.48550/arxiv.2011.06964

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

Autorzy: Tao, Qinghua; Li, Z; Xu, J; Lin, S; De Schutter, Bart; Suykens, J
Opublikowane w: Ieee Transactions On Intelligent Transportation Systems; 2022, Numer Vol. 23; iss. 9, 2022, ISSN 1524-9050
Wydawca: Institute of Electrical and Electronics Engineers
DOI: 10.1109/tits.2022.3142728

Deep kernel principal component analysis for multi-level feature learning

Autorzy: Tonin, F; Tao, Q; Patrinos, Panagiotis; Suykens, J
Opublikowane w: Neural Networks, Numer 2024; Vol. 170; pp. 578 - 595, 2024, ISSN 0893-6080
Wydawca: Pergamon Press Ltd.
DOI: 10.1016/j.neunet.2023.11.045

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

Autorzy: Jun Xu, Qinghua Tao, Zhen Li, Xiangming Xi, Johan A.K. Suykens, Shuning Wang
Opublikowane w: Automatica, Numer 116, 2020, Strona(/y) 108906, ISSN 0005-1098
Wydawca: Pergamon Press Ltd.
DOI: 10.1016/j.automatica.2020.108906

Tensor-based restricted kernel machines for multi-view classification

Autorzy: Lynn Houthuys, Johan A.K. Suykens
Opublikowane w: Information Fusion, Numer 68, 2021, Strona(/y) 54-66, ISSN 1566-2535
Wydawca: Elsevier BV
DOI: 10.1016/j.inffus.2020.10.022

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