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1دورية أكاديمية
المؤلفون: Zahra Karevan, Johan A. K. Suykens
المصدر: Entropy, Vol 20, Iss 4, p 264 (2018)
مصطلحات موضوعية: transductive learning, conditional entropy, information transfer, feature selection, weather forecasting, Science, Astrophysics, QB460-466, Physics, QC1-999
وصف الملف: electronic resource
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2دورية أكاديمية
المؤلفون: Yuning Yang, Yunlong Feng, Johan A. K. Suykens
المصدر: Entropy, Vol 20, Iss 3, p 171 (2018)
مصطلحات موضوعية: robust matrix completion, hard/soft iterative thresholding, non-Gaussian noise, outliers, linear convergence, Science, Astrophysics, QB460-466, Physics, QC1-999
وصف الملف: electronic resource
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3دورية أكاديمية
المؤلفون: Rocco Langone, Marc Van Barel, Johan A. K. Suykens
المصدر: Entropy, Vol 18, Iss 5, p 182 (2016)
مصطلحات موضوعية: spectral clustering, incomplete Cholesky decomposition, normalized mutual information, Science, Astrophysics, QB460-466, Physics, QC1-999
وصف الملف: electronic resource
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4
المؤلفون: Xiaoli Li, Zhen Li, Qinghua Tao, Jun Xu, Shuning Wang, Johan A. K. Suykens, Na Xie
المصدر: IEEE Transactions on Neural Networks and Learning Systems
مصطلحات موضوعية: Neurons, Optimization problem, Artificial neural network, Computer Networks and Communications, Computer science, System identification, Brain, Convexity, Backpropagation, Domain (mathematical analysis), Computer Science Applications, Tree structure, Hyperplane, Artificial Intelligence, Neural Networks, Computer, Algorithm, Algorithms, Software
وصف الملف: Print-Electronic
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5
المؤلفون: Michaël Fanuel, Joachim Schreurs, Johan A. K. Suykens
المصدر: SIAM Journal on Mathematics of Data Science. 4:1171-1190
URL الوصول: https://explore.openaire.eu/search/publication?articleId=doi_________::813603c16a565be8fac1ca92e0925122
https://doi.org/10.1137/21m1403977 -
6دورية أكاديمية
المصدر: PLoS ONE, Vol 14, Iss 6, p e0217967 (2019)
وصف الملف: electronic resource
Relation: https://doaj.org/toc/1932-6203
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7
المؤلفون: Mei Xie, Xin Ma, Johan A. K. Suykens
المصدر: Neurocomputing. 456:61-75
مصطلحات موضوعية: Structure (mathematical logic), 0209 industrial biotechnology, Generality, business.industry, Computer science, Cognitive Neuroscience, 02 engineering and technology, Large scale data, Machine learning, computer.software_genre, Bayesian interpretation of regularization, Computer Science Applications, System model, Variety (cybernetics), 020901 industrial engineering & automation, Artificial Intelligence, 0202 electrical engineering, electronic engineering, information engineering, 020201 artificial intelligence & image processing, Artificial intelligence, business, computer, High potential
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8
المؤلفون: Joachim Schreurs, Michaël Fanuel, Johan A. K. Suykens
المصدر: SIAM Journal on Mathematics of Data Science
مصطلحات موضوعية: FOS: Computer and information sciences, Computer Science - Machine Learning, Scale (ratio), Computer science, 0211 other engineering and technologies, Sampling (statistics), Machine Learning (stat.ML), 021107 urban & regional planning, 02 engineering and technology, 01 natural sciences, Regularization (mathematics), Regression, Machine Learning (cs.LG), 010104 statistics & probability, Kernel method, Statistics - Machine Learning, Kernel (statistics), Nyström method, Determinantal point process, 0101 mathematics, Algorithm
URL الوصول: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::393ed17fa8895ada25202087e02bf60a
https://doi.org/10.1137/20m1320031 -
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المساهمون: Centre National de la Recherche Scientifique (CNRS), Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 (CRIStAL), Université de Lille-Centrale Lille-Centre National de la Recherche Scientifique (CNRS), Université Catholique de Louvain = Catholic University of Louvain (UCL), Ecole Polytechnique de Louvain (EPL), Department of Electrical Engineering [KU Leuven] (KU-ESAT), Catholic University of Leuven - Katholieke Universiteit Leuven (KU Leuven), Center for Dynamical Systems, Signal Processing and Data Analytics (ESAT-STADIUS), Centrale Lille-Université de Lille-Centre National de la Recherche Scientifique (CNRS), UCL - SST/ICTM - Institute of Information and Communication Technologies, Electronics and Applied Mathematics
المصدر: SIAM Journal on Mathematics of Data Science, Vol. 4, no.1, p. 153–178 (2022)
مصطلحات موضوعية: FOS: Computer and information sciences, Computer Science - Machine Learning, [SPI]Engineering Sciences [physics], Statistics - Machine Learning, Machine Learning (stat.ML), [INFO]Computer Science [cs], [MATH]Mathematics [math], Machine Learning (cs.LG)
URL الوصول: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0ebec2bff2d8fe64b262a31c4ac4cfcc
https://hal.archives-ouvertes.fr/hal-03511366 -
10
المؤلفون: Michaël Fanuel, Joachim Schreurs, Johan A. K. Suykens
المساهمون: Centre National de la Recherche Scientifique (CNRS), Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 (CRIStAL), Centrale Lille-Université de Lille-Centre National de la Recherche Scientifique (CNRS), Department of Electrical Engineering [KU Leuven] (KU-ESAT), Catholic University of Leuven - Katholieke Universiteit Leuven (KU Leuven), Center for Dynamical Systems, Signal Processing and Data Analytics (ESAT-STADIUS), Université de Lille-Centrale Lille-Centre National de la Recherche Scientifique (CNRS)
مصطلحات موضوعية: Computer Science - Machine Learning, [SPI]Engineering Sciences [physics], Artificial Intelligence, Statistics - Machine Learning, [INFO]Computer Science [cs], [MATH]Mathematics [math], Software
URL الوصول: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::310e5e55540c516e526d49c1c04e7d4d
https://hal.science/hal-03511384