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1Conference
المؤلفون: Tran, Thi-Minh-Dung, Kibangou, Alain
المساهمون: Networked Controlled Systems (NECS), Inria Grenoble - Rhône-Alpes, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Département Automatique (GIPSA-DA), Grenoble Images Parole Signal Automatique (GIPSA-lab), Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Stendhal - Grenoble 3-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP)-Centre National de la Recherche Scientifique (CNRS)-Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Stendhal - Grenoble 3-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP)-Centre National de la Recherche Scientifique (CNRS)-Grenoble Images Parole Signal Automatique (GIPSA-lab), Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Stendhal - Grenoble 3-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP)-Centre National de la Recherche Scientifique (CNRS)-Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Stendhal - Grenoble 3-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP)-Centre National de la Recherche Scientifique (CNRS)
المصدر: EUSIPCO 2015 - 23th European Signal Processing Conference ; https://hal.science/hal-01167337 ; EUSIPCO 2015 - 23th European Signal Processing Conference, Aug 2015, Nice, France
مصطلحات موضوعية: Network topology Reconstruction, Graph Laplacian spectrum, Eigenvectors, Anonymous nodes, Average Consensus, [SPI.AUTO]Engineering Sciences [physics]/Automatic, [INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing
Time: Nice, France
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2
المؤلفون: Maurizio Brunetti
المساهمون: Brunetti, M
المصدر: Theory and Applications of Graphs, Vol 7, Iss 2 (2020)
مصطلحات موضوعية: Numerical Analysis, Laplacian spectrum, spiked triangle, lcsh:Mathematics, Spectral properties, laplacian spectrum, lcsh:QA1-939, Theoretical Computer Science, Combinatorics, signed graph, pendant vertex, Discrete Mathematics and Combinatorics, Signed graph, Laplacian spectrum, pendant vertex, circular caterpillar, spiked triangle, Signed graph, Laplace operator, circular caterpillar, Mathematics
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3
المساهمون: Avrachenkov, Konstantin, Cottatellucci, Laura, Hamidouche, Mounia
المصدر: COMPLEX NETWORKS 2019, 8th International Conference on Complex Networks and their Applications, 10-12 December 2019, Lisbon, Portugal
مصطلحات موضوعية: Random geometric graph, Laplacian spectrum, Spectral dimension
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4
المؤلفون: Calandriello, Daniele
المساهمون: Sequential Learning (SEQUEL), Inria Lille - Nord Europe, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-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)-Centrale Lille-Université de Lille-Centre National de la Recherche Scientifique (CNRS), Inria Lille Nord Europe - Laboratoire CRIStAL - Université de Lille, Michal Valko, Alessandro Lazaric
المصدر: Machine Learning [cs.LG]. Inria Lille Nord Europe-Laboratoire CRIStAL-Université de Lille, 2017. English. ⟨NNT : ⟩
Machine Learning [cs.LG]. Inria Lille Nord Europe-Laboratoire CRIStAL-Université de Lille, 2017. Englishمصطلحات موضوعية: Stochastic gradient method, Distributed learning, ACM: G.: Mathematics of Computing/G.2: DISCRETE MATHEMATICS/G.2.2: Graph Theory/G.2.2.1: Graph labeling, Principal component analysis method, Newton and quasi-Newton methods, Sequential learning, Kernel learning, ACM: G.: Mathematics of Computing/G.1: NUMERICAL ANALYSIS/G.1.6: Optimization/G.1.6.1: Convex programming, ACM: G.: Mathematics of Computing/G.1: NUMERICAL ANALYSIS/G.1.3: Numerical Linear Algebra, Nystrom-type algorithm, Dictionary learning, ACM: I.: Computing Methodologies/I.2: ARTIFICIAL INTELLIGENCE/I.2.11: Distributed Artificial Intelligence, [INFO.INFO-NA]Computer Science [cs]/Numerical Analysis [cs.NA], Low-rank Matrix Approximation, Apprentissage, Nystrom approximation, ACM: G.: Mathematics of Computing/G.2: DISCRETE MATHEMATICS/G.2.2: Graph Theory, [INFO.INFO-LG]Computer Science [cs]/Machine Learning [cs.LG], [STAT.ML]Statistics [stat]/Machine Learning [stat.ML], Online learning, Semi-supervised learning, ACM: G.: Mathematics of Computing/G.1: NUMERICAL ANALYSIS/G.1.6: Optimization/G.1.6.3: Gradient methods, Graph Laplacian spectrum, Gaussian process, ACM: I.: Computing Methodologies/I.2: ARTIFICIAL INTELLIGENCE/I.2.6: Learning
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5Dissertation/ Thesis
المؤلفون: Calandriello, Daniele
المساهمون: Sequential Learning (SEQUEL), Inria Lille - Nord Europe, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-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)-Centrale Lille-Université de Lille-Centre National de la Recherche Scientifique (CNRS), Inria Lille Nord Europe - Laboratoire CRIStAL - Université de Lille, Michal Valko, Alessandro Lazaric
المصدر: https://theses.hal.science/tel-01816904 ; Machine Learning [cs.LG]. Inria Lille Nord Europe - Laboratoire CRIStAL - Université de Lille, 2017. English. ⟨NNT : ⟩.
مصطلحات موضوعية: Nystrom approximation, Nystrom-type algorithm, Sequential learning, Stochastic gradient method, Newton and quasi-Newton methods, Graph Laplacian spectrum, Semi-supervised learning, Kernel learning, Gaussian process, Low-rank Matrix Approximation, Distributed learning, Dictionary learning, Principal component analysis method, Online learning, Apprentissage, ACM: I.: Computing Methodologies/I.2: ARTIFICIAL INTELLIGENCE/I.2.6: Learning, ACM: I.: Computing Methodologies/I.2: ARTIFICIAL INTELLIGENCE/I.2.11: Distributed Artificial Intelligence, ACM: G.: Mathematics of Computing/G.1: NUMERICAL ANALYSIS/G.1.3: Numerical Linear Algebra, ACM: G.: Mathematics of Computing/G.1: NUMERICAL ANALYSIS/G.1.6: Optimization/G.1.6.3: Gradient methods, ACM: G.: Mathematics of Computing/G.1: NUMERICAL ANALYSIS/G.1.6: Optimization/G.1.6.1: Convex programming, ACM: G.: Mathematics of Computing/G.2: DISCRETE MATHEMATICS/G.2.2: Graph Theory/G.2.2.1: Graph labeling, ACM: G.: Mathematics of Computing/G.2: DISCRETE MATHEMATICS/G.2.2: Graph Theory, [INFO.INFO-LG]Computer Science [cs]/Machine Learning [cs.LG], [STAT.ML]Statistics [stat]/Machine Learning [stat.ML], [INFO.INFO-NA]Computer Science [cs]/Numerical Analysis [cs.NA]