Search Results - "Kernel methods"

Effective non-random extreme learning machine

Authors: Daniela De Canditiis Fabiano Veglianti

Source: Neural Computing and Applications. 37:20691-20719

Subject Terms: Machine Learning, FOS: Computer and information sciences, elm, kernel methods, random feature learning, nonparametric regression, Machine Learning (stat.ML), Machine Learning (cs.LG)

File Description: application/pdf

Access URL: http://arxiv.org/abs/2411.16229

Be greedy and learn: efficient and certified algorithms for parametrized optimal control problems

Authors: Hendrik Kleikamp Martin Lazar Cesare Molinari

Source: ESAIM: Mathematical Modelling and Numerical Analysis. 59:291-330

Subject Terms: greedy methods, parametrized optimal control, Numerical Analysis (math.NA), reduced basis, greedy algorithm, kernel methods, optimal control, 49N10, 68T07, 46E22, 62J02, machine learning, deep neural networks, Optimization and Control (math.OC), error estimation, FOS: Mathematics, Mathematics - Numerical Analysis, Deep neural networks, Error estimation, Greedy algorithm, Kernel methods, Machine learning, Parametrized optimal control, Mathematics - Optimization and Control

Access URL: http://arxiv.org/abs/2307.15590
https://hdl.handle.net/11567/1254217
https://doi.org/10.1051/m2an/2024074

Kernel approaches for complex phenotype prediction

Authors: Ramon Gurrea, Elies

Thesis Advisors: Belanche Muñoz, Lluís A. (Lluís Antoni), Pérez Enciso, Miguel, Barbadilla Prados, Antonio

Source: TDX (Tesis Doctorals en Xarxa)

Subject Terms: Fenotip, Fenotipo, Phenotype, Predicció, Predicción, Prediction, Mètodes Kernel, Métodos Kernel, Kernel Methods, Ciències Experimentals

File Description: application/pdf

Access URL: http://hdl.handle.net/10803/671296

Regularized Identification with Internal Positivity Side-Information: Regularized identification with internal positivity side-information

Authors: Mohammad Khosravi Roy S. Smith

Source: SIAM Journal on Control and Optimization. 63:26-56

Subject Terms: positive systems, 0209 industrial biotechnology, Positive control/observation systems, Kernel methods, 02 engineering and technology, Systems and Control (eess.SY), Electrical Engineering and Systems Science - Systems and Control, Positive systems, kernel methods, Optimization and Control (math.OC), 0202 electrical engineering, electronic engineering, information engineering, FOS: Electrical engineering, electronic engineering, information engineering, FOS: Mathematics, Control/observation systems in abstract spaces, Hilbert spaces with reproducing kernels (= (proper) functional Hilbert spaces, including de Branges-Rovnyak and other structured spaces), System identification, Mathematics - Optimization and Control, system identification

File Description: application/xml

Access URL: http://arxiv.org/abs/2111.00407

Uplink Non-Orthogonal Multiple Access (NOMA) Decoding Based on Successive Parzen Windows Interference Cancellation

Authors: Víctor P. Gil Jiménez Ángel Navia Vázquez Agencia Estatal de Investigación (España)

Contributors: Víctor P. Gil Jiménez Ángel Navia Vázquez Agencia Estatal de Investigación (España)

Source: e-Archivo. Repositorio Institucional de la Universidad Carlos III de Madrid
Universidad Carlos III de Madrid (UC3M)
IEEE Open Journal of Vehicular Technology, Vol 6, Pp 265-275 (2025)

Subject Terms: SIC, 3D antena, parzen windows, Telecomunicaciones, TA1001-1280, multi-user interference, NOMA, Kernel methods, 3D antenna, Transportation engineering, Multi-user interference, kernel methods, Mimo, Parzen windows, Transportation and communications, HE1-9990, 6G

File Description: application/pdf

Access URL: https://hdl.handle.net/10016/47825
https://doaj.org/article/414a19e830114489a1acf7176d19d56c

Expressivity vs. Generalization in Quantum Kernel Methods

Authors: Gross, Markus Lange, Markus Bujnowski, Bogusz et al.

Source: ESANN 2025 proceesdings. :543-548

Subject Terms: Kernel Methods, Quantum Machine Learning

Access URL: https://elib.dlr.de/214322/
https://doi.org/10.14428/esann/2025.es2025-152

Approximate‐Guided Representation Learning in Vision Transformer

Authors: Kaili Wang Xinwei Sun Huijie He et al.

Source: CAAI Transactions on Intelligence Technology, Vol 10, Iss 5, Pp 1459-1477 (2025)

Subject Terms: computer vision, deep learning, image representation, kernel methods, rough sets, Computational linguistics. Natural language processing, P98-98.5, Computer software, QA76.75-76.765

File Description: electronic resource

Relation: https://doaj.org/toc/2468-2322

Access URL: https://doaj.org/article/2852b6fa7f4e4873a7dc223373011b48

A New Canonical Log-Euclidean Kernel for Symmetric Positive Definite Matrices for EEG Analysis (Oct 2024)

Authors: Gabriel Leander Wagner vom Berg Vera Röhr Daniel Platt et al.

Source: IEEE Transactions on Biomedical Engineering. 72:1000-1007

Subject Terms: kernel methods, motor imagery, symmetric positive definite matrices, Brain-Computer Interfaces, Humans, Brain, Electroencephalography, Signal Processing, Computer-Assisted, log-Euclidean metric, EEG analysis, Riemannian geometry, Algorithms, 600 Technik, Medizin, angewandte Wissenschaften::610 Medizin und Gesundheit::610 Medizin und Gesundheit

Access URL: https://pubmed.ncbi.nlm.nih.gov/40031582

Scalable Nonparametric Supervised Learning for Streaming and Massive Data: Applications in Healthcare Monitoring and Credit Risk

Authors: Mohamed Chaouch Omama M. Al-Hamed

Source: IEEE Access, Vol 13, Pp 131716-131732 (2025)

Subject Terms: kernel methods, nonparametric statistics, Big data applications, machine learning, classification algorithms, Electrical engineering. Electronics. Nuclear engineering, dimensionality reduction, TK1-9971

Access URL: https://doaj.org/article/009712611eb940eba391f4a2b405182f

Enhancing Text Classification Through Quantum Transfer Learning: A Hybrid Quantum-Classical Approach With Complex Kernel Self-Attention Networks

Authors: Xiaoxiao Chen Xiaoping Lou

Source: IEEE Access, Vol 13, Pp 133882-133890 (2025)

Subject Terms: text classification, quantum kernel methods, quantum transfer learning, Electrical engineering. Electronics. Nuclear engineering, hybrid neural networks, Quantum machine learning, TK1-9971

Access URL: https://doaj.org/article/49b9c4acc9bf4414921e1a4939d2ec50

Multi-Kernel Learning for Heterogeneous Data

Authors: Chunlan Liao Shili Peng

Source: IEEE Access, Vol 13, Pp 45340-45349 (2025)

Subject Terms: kernel methods, Multi-kernel learning, mixed data, support vector machine, categorical data, Electrical engineering. Electronics. Nuclear engineering, TK1-9971

Access URL: https://doaj.org/article/1fc38e7cedd44dc28c2f93321d6b7017

Conditional Dependence via U-Statistics Pruning

Authors: Cabrera Estanyol, Ferran de Vila Insa, Marc Riba Sagarra, Jaume

Source: UPCommons. Portal del coneixement obert de la UPC
Universitat Politècnica de Catalunya (UPC)

Subject Terms: FOS: Computer and information sciences, Hilbert-Schmidt independence criterion (HSIC), Conditional dependence, U-Statistics, Statistics - Machine Learning, Computer Science - Information Theory, Information Theory (cs.IT), G.3, Kernel methods, Machine Learning (stat.ML), Àrees temàtiques de la UPC::Enginyeria de la telecomunicació::Processament del senyal

File Description: application/pdf

Access URL: http://arxiv.org/abs/2410.15888

A Comparison Study of Supervised Learning Techniques for the Approximation of High Dimensional Functions and Feedback Control

Authors: Oster M. Saluzzi L. Wenzel T.

Source: 29 Seiten (2024). doi:10.48550/arXiv.2402.01402

Subject Terms: Kernel Methods, Optimal control, High-dimensionality, Neural networks, Kernel methods, Tensor trains, High-Dimensionality, Neural Networks, Tensor Trains, Optimal Control, Mathematics - Numerical Analysis, Mathematics - Optimization and Control

Access URL: http://arxiv.org/abs/2402.01402
https://publications.rwth-aachen.de/record/981225

Revisiting Total Model Errors and Model Validation

Authors: Ljung, Lennart

Source: Journal of Systems Science and Complexity. 34(5):1598-1603

Subject Terms: Bias, kernel methods, model errors, regularization, system identification, variance

File Description: electronic

Access URL: https://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-180879
https://liu.diva-portal.org/smash/get/diva2:1609269/FULLTEXT01.pdf

Quantum Kernel Methods for Insar Phase Unwrapping

Authors: Glatting, Kay Meyer, Jan Huber, Sigurd et al.

Source: IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium. :437-441

Subject Terms: InSAR, Phase Unwrapping, Quantum Computing, Quantum Kernel Methods

Recent kernel methods for interacting particle systems: first numerical results

Authors: Christian Fiedler Michael Herty Chiara Segala et al.

Source: European Journal of Applied Mathematics, Vol 36, Pp 464-489 (2025)
European journal of applied mathematics 36(2), 464-489 (2024). doi:10.1017/S0956792524000706 special issue: "From integro-differential models to data-oriented approaches for emergent phenomena / Seung-Yeal Ha; Qin Li; Andrea Tosin; Mattia Zanella"

Subject Terms: interacting particle systems, 82B40, kernel methods, machine learning, 82C40, QA1-939, 93A16, mean-field limit, 0101 mathematics, 01 natural sciences, 46E22, Mathematics

Access URL: https://doaj.org/article/a9cc5048d7d6447d8f5fbaaf746cca8d
https://publications.rwth-aachen.de/record/1000113

Data-Driven Observability Analysis for Nonlinear Stochastic Systems

Authors: Pierre-François Massiani Mona Buisson-Fenet Friedrich Solowjow et al.

Contributors: Pierre-François Massiani Mona Buisson-Fenet Friedrich Solowjow et al.

Source: IEEE Transactions on Automatic Control. 69:4042-4049

Subject Terms: FOS: Computer and information sciences, Computer Science - Machine Learning, 0209 industrial biotechnology, stochastic systems, Kernel methods, 02 engineering and technology, Systems and Control (eess.SY), Electrical Engineering and Systems Science - Systems and Control, Machine Learning (cs.LG), statistical learning, [INFO.INFO-AU]Computer Science [cs]/Automatic Control Engineering, FOS: Electrical engineering, electronic engineering, information engineering, Kernel methods nonlinear systems output feedback and observers statistical learning stochastic systems, nonlinear systems, output feedback and observers

Access URL: http://arxiv.org/abs/2302.11979

A shift in paradigm for system identification

Authors: Ljung, Lennart Chen, Tianshi Mu, Biqiang

Source: International Journal of Control. 93(2):173-180

Subject Terms: System identification, linear regressions, bias-variance tradeoff, regularisation, kernel methods

File Description: electronic

Access URL: https://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-164209
https://liu.diva-portal.org/smash/get/diva2:1413453/FULLTEXT01.pdf

A bias-variance perspective of data-driven control

Authors: Colin, Kevin Ju, Yue Bombois, Xavier et al.

Source: IFAC-Papers OnLine. :85-90

Subject Terms: Bayes control, Data-driven control, Kernel Methods, Regularization

File Description: print

Access URL: https://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-354904
https://doi.org/10.1016/j.ifacol.2024.08.509

Parallel-in-Time Probabilistic Solutions for Time-Dependent Nonlinear Partial Differential Equations

Authors: Iqbal, Sahel Abdulsamad, Hany Cator, Tripp et al.

Contributors: Iqbal, Sahel Abdulsamad, Hany Cator, Tripp et al.

Source: 2024 IEEE 34th International Workshop on Machine Learning for Signal Processing (MLSP). :1-6

Subject Terms: kernel methods, parallel algorithm, probabilistic numerics, partial differential equations, parallel computation, sparse optimization

File Description: application/pdf

Access URL: https://aaltodoc.aalto.fi/handle/123456789/131950