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Artykuły w czasopismach na temat "Subspaces methods"
Eiermann, Michael, i Oliver G. Ernst. "Geometric aspects of the theory of Krylov subspace methods". Acta Numerica 10 (maj 2001): 251–312. http://dx.doi.org/10.1017/s0962492901000046.
Pełny tekst źródłaFreund, Roland W. "Model reduction methods based on Krylov subspaces". Acta Numerica 12 (maj 2003): 267–319. http://dx.doi.org/10.1017/s0962492902000120.
Pełny tekst źródłaSia, Florence, i Rayner Alfred. "Tree-based mining contrast subspace". International Journal of Advances in Intelligent Informatics 5, nr 2 (23.07.2019): 169. http://dx.doi.org/10.26555/ijain.v5i2.359.
Pełny tekst źródłaLENG, JINSONG, i ZHIHU HUANG. "OUTLIERS DETECTION WITH CORRELATED SUBSPACES FOR HIGH DIMENSIONAL DATASETS". International Journal of Wavelets, Multiresolution and Information Processing 09, nr 02 (marzec 2011): 227–36. http://dx.doi.org/10.1142/s0219691311004067.
Pełny tekst źródłaLaaksonen, Jorma, i Erkki Oja. "Learning Subspace Classifiers and Error-Corrective Feature Extraction". International Journal of Pattern Recognition and Artificial Intelligence 12, nr 04 (czerwiec 1998): 423–36. http://dx.doi.org/10.1142/s0218001498000270.
Pełny tekst źródłaSeshadri, P., S. Yuchi, G. T. Parks i S. Shahpar. "Supporting multi-point fan design with dimension reduction". Aeronautical Journal 124, nr 1279 (27.07.2020): 1371–98. http://dx.doi.org/10.1017/aer.2020.50.
Pełny tekst źródłaNagi, Sajid, Dhruba Kumar Bhattacharyya i Jugal K. Kalita. "A Preview on Subspace Clustering of High Dimensional Data". INTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY 6, nr 3 (21.05.2013): 441–48. http://dx.doi.org/10.24297/ijct.v6i3.4466.
Pełny tekst źródłaZhou, Jie, Chucheng Huang, Can Gao, Yangbo Wang, Xinrui Shen i Xu Wu. "Weighted Subspace Fuzzy Clustering with Adaptive Projection". International Journal of Intelligent Systems 2024 (31.01.2024): 1–18. http://dx.doi.org/10.1155/2024/6696775.
Pełny tekst źródłaPang, Guansong, Kai Ming Ting, David Albrecht i Huidong Jin. "ZERO++: Harnessing the Power of Zero Appearances to Detect Anomalies in Large-Scale Data Sets". Journal of Artificial Intelligence Research 57 (29.12.2016): 593–620. http://dx.doi.org/10.1613/jair.5228.
Pełny tekst źródłaIl’in, V. P. "Projection Methods in Krylov Subspaces". Journal of Mathematical Sciences 240, nr 6 (28.06.2019): 772–82. http://dx.doi.org/10.1007/s10958-019-04395-7.
Pełny tekst źródłaRozprawy doktorskie na temat "Subspaces methods"
Shank, Stephen David. "Low-rank solution methods for large-scale linear matrix equations". Diss., Temple University Libraries, 2014. http://cdm16002.contentdm.oclc.org/cdm/ref/collection/p245801coll10/id/273331.
Pełny tekst źródłaPh.D.
We consider low-rank solution methods for certain classes of large-scale linear matrix equations. Our aim is to adapt existing low-rank solution methods based on standard, extended and rational Krylov subspaces to solve equations which may viewed as extensions of the classical Lyapunov and Sylvester equations. The first class of matrix equations that we consider are constrained Sylvester equations, which essentially consist of Sylvester's equation along with a constraint on the solution matrix. These therefore constitute a system of matrix equations. The second are generalized Lyapunov equations, which are Lyapunov equations with additional terms. Such equations arise as computational bottlenecks in model order reduction.
Temple University--Theses
UGWU, UGOCHUKWU OBINNA. "Iterative tensor factorization based on Krylov subspace-type methods with applications to image processing". Kent State University / OhioLINK, 2021. http://rave.ohiolink.edu/etdc/view?acc_num=kent1633531487559183.
Pełny tekst źródłaHossain, Mohammad Sahadet. "Numerical Methods for Model Reduction of Time-Varying Descriptor Systems". Doctoral thesis, Universitätsbibliothek Chemnitz, 2011. http://nbn-resolving.de/urn:nbn:de:bsz:ch1-qucosa-74776.
Pełny tekst źródłaAhmed, Nisar. "Implicit restart schemes for Krylov subspace model reduction methods". Thesis, Imperial College London, 1999. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.340535.
Pełny tekst źródłaShatnawi, Heba Awad Addad. "Frequency estimation using subspace methods". Thesis, Wichita State University, 2009. http://hdl.handle.net/10057/2419.
Pełny tekst źródłaThesis (M.S.)--Wichita State University, College of Engineering, Dept. of Electrical and Computer Engineering
Ensor, Jonathan Edward. "Subspace methods for eigenstructure assignment". Thesis, University of York, 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.341821.
Pełny tekst źródłaMestrah, Ali. "Identification de modèles sous forme de représentation d'état pour les systèmes à sortie binaire". Electronic Thesis or Diss., Normandie, 2023. http://www.theses.fr/2023NORMC255.
Pełny tekst źródłaThis thesis focuses on parametric modeling of invariant linear systems from binary output measurements. This identification problem is addressed via the use ofsubspace methods. These methods allow the estimation of state-space models, an added benefit of these methods being the fact that their implementation doesnot require the prior knowledge of the order of the system. These methods are initially adapted to high resolution data processing, the objective of this thesis istherefore their adaptation to the identification using binary measurements. In this thesis we propose three subspace methods. Convergence properties of two ofthem are established. Monte Carlo simulation results are presented to show the good performance, but also limits, of these methods
Nguyen, Hieu. "Linear subspace methods in face recognition". Thesis, University of Nottingham, 2011. http://eprints.nottingham.ac.uk/12330/.
Pełny tekst źródłaTao, Dacheng. "Discriminative linear and multilinear subspace methods". Thesis, Birkbeck (University of London), 2007. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.438996.
Pełny tekst źródłaYu, Xuebo. "Generalized Krylov subspace methods with applications". Kent State University / OhioLINK, 2014. http://rave.ohiolink.edu/etdc/view?acc_num=kent1401937618.
Pełny tekst źródłaKsiążki na temat "Subspaces methods"
Demmel, James Weldon. Three methods for refining estimates of invariant subspaces. New York: Courant Institute of Mathematical Sciences, New York University, 1985.
Znajdź pełny tekst źródłaWatkins, David S. The matrix eigenvalue problem: GR and Krylov subspace methods. Philadelphia: Society for Industrial and Applied Mathematics, 2007.
Znajdź pełny tekst źródłaMats, Viberg, i Stoica Petre 1949-, red. Subspace methods. Amsterdam: Elsevier, 1996.
Znajdź pełny tekst źródłaKatayama, Tohru. Subspace methods for system identification. London: Springer, 2005.
Znajdź pełny tekst źródłaKatayama, Tohru. Subspace Methods for System Identification. London: Springer London, 2005. http://dx.doi.org/10.1007/1-84628-158-x.
Pełny tekst źródłaSaad, Y. Krylov subspace methods on supercomputers. [Moffett Field, Calif.?]: Research Institute for Advanced Computer Science, NASA Ames Research Center, 1988.
Znajdź pełny tekst źródłaSogabe, Tomohiro. Krylov Subspace Methods for Linear Systems. Singapore: Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-8532-4.
Pełny tekst źródłaHeeger, David J. Subspace methods for recovering rigid motion. Toronto, Ont: University of Toronto, 1990.
Znajdź pełny tekst źródłaJepson, Allan D. Linear subspace methods for recovering translational direction. Toronto: University of Toronto, Dept. of Computer Science, 1992.
Znajdź pełny tekst źródłaF, Chan Tony, i Research Institute for Advanced Computer Science (U.S.), red. Preserving symmetry in preconditioned Krylov subspace methods. [Moffett Field, Calif.]: Research Institute for Advanced Computer Science, NASA Ames Research Center, 1996.
Znajdź pełny tekst źródłaCzęści książek na temat "Subspaces methods"
Schechter, Martin. "Estimates on Subspaces". W Linking Methods in Critical Point Theory, 131–44. Boston, MA: Birkhäuser Boston, 1999. http://dx.doi.org/10.1007/978-1-4612-1596-7_6.
Pełny tekst źródłaDowney, R. G., i Jeffrey B. Remmel. "Effectively and Noneffectively Nowhere Simple Subspaces". W Logical Methods, 314–51. Boston, MA: Birkhäuser Boston, 1993. http://dx.doi.org/10.1007/978-1-4612-0325-4_10.
Pełny tekst źródłaNenciu, G. "Almost Invariant Subspaces for Quantum Evolutions". W Multiscale Methods in Quantum Mechanics, 83–97. Boston, MA: Birkhäuser Boston, 2004. http://dx.doi.org/10.1007/978-0-8176-8202-6_7.
Pełny tekst źródłaFischer, Bernd. "Orthogonal Polynomials and Krylov Subspaces". W Polynomial Based Iteration Methods for Symmetric Linear Systems, 132–36. Wiesbaden: Vieweg+Teubner Verlag, 1996. http://dx.doi.org/10.1007/978-3-663-11108-5_4.
Pełny tekst źródłaFroelich, John, i Michael Marsalli. "Operator Semigroups, Invariant Sets and Invariant Subspaces". W Algebraic Methods in Operator Theory, 10–14. Boston, MA: Birkhäuser Boston, 1994. http://dx.doi.org/10.1007/978-1-4612-0255-4_2.
Pełny tekst źródłaIlin, Valery P. "Multi-preconditioned Domain Decomposition Methods in the Krylov Subspaces". W Lecture Notes in Computer Science, 95–106. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-57099-0_9.
Pełny tekst źródłaAnton, Cristina, i Iain Smith. "Model Based Clustering of Functional Data with Mild Outliers". W Studies in Classification, Data Analysis, and Knowledge Organization, 11–19. Cham: Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-09034-9_2.
Pełny tekst źródłaBoot, Tom, i Didier Nibbering. "Subspace Methods". W Macroeconomic Forecasting in the Era of Big Data, 267–91. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-31150-6_9.
Pełny tekst źródłaFukui, Kazuhiro. "Subspace Methods". W Computer Vision, 1–5. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-03243-2_708-1.
Pełny tekst źródłaFukui, Kazuhiro. "Subspace Methods". W Computer Vision, 777–81. Boston, MA: Springer US, 2014. http://dx.doi.org/10.1007/978-0-387-31439-6_708.
Pełny tekst źródłaStreszczenia konferencji na temat "Subspaces methods"
Zhou, Lei, Xiao Bai, Dong Wang, Xianglong Liu, Jun Zhou i Edwin Hancock. "Latent Distribution Preserving Deep Subspace Clustering". W Twenty-Eighth International Joint Conference on Artificial Intelligence {IJCAI-19}. California: International Joint Conferences on Artificial Intelligence Organization, 2019. http://dx.doi.org/10.24963/ijcai.2019/617.
Pełny tekst źródłaRenaud, J. E., i G. A. Gabriele. "Sequential Global Approximation in Non-Hierarchic System Decomposition and Optimization". W ASME 1991 Design Technical Conferences. American Society of Mechanical Engineers, 1991. http://dx.doi.org/10.1115/detc1991-0086.
Pełny tekst źródłaYing, Shihui, Lipeng Cai, Changzhou He i Yaxin Peng. "Geometric Understanding for Unsupervised Subspace Learning". W Twenty-Eighth International Joint Conference on Artificial Intelligence {IJCAI-19}. California: International Joint Conferences on Artificial Intelligence Organization, 2019. http://dx.doi.org/10.24963/ijcai.2019/579.
Pełny tekst źródłaTripathy, Rohit, i Ilias Bilionis. "Deep Active Subspaces: A Scalable Method for High-Dimensional Uncertainty Propagation". W ASME 2019 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2019. http://dx.doi.org/10.1115/detc2019-98099.
Pełny tekst źródłaArora, Akhil, Alberto Garcia-Duran i Robert West. "Low-Rank Subspaces for Unsupervised Entity Linking". W Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing. Stroudsburg, PA, USA: Association for Computational Linguistics, 2021. http://dx.doi.org/10.18653/v1/2021.emnlp-main.634.
Pełny tekst źródłaXie, Zhihui, Handong Zhao, Tong Yu i Shuai Li. "Discovering Low-rank Subspaces for Language-agnostic Multilingual Representations". W Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing. Stroudsburg, PA, USA: Association for Computational Linguistics, 2022. http://dx.doi.org/10.18653/v1/2022.emnlp-main.379.
Pełny tekst źródłaSmith, Malcolm J., T. S. Koko i I. R. Orisamolu. "Comparative Assessment of Optimal Control Methods With Integrated Performance Constraints". W ASME 1998 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 1998. http://dx.doi.org/10.1115/imece1998-0947.
Pełny tekst źródłaBahamonde, Juan S., Matteo Pini i Piero Colonna. "ACTIVE SUBSPACES FOR THE PRELIMINARY FLUID DYNAMIC DESIGN OF UNCONVENTIONAL TURBOMACHINERY". W VII European Congress on Computational Methods in Applied Sciences and Engineering. Athens: Institute of Structural Analysis and Antiseismic Research School of Civil Engineering National Technical University of Athens (NTUA) Greece, 2016. http://dx.doi.org/10.7712/100016.2433.7806.
Pełny tekst źródłaAl-Seraji, Najm Abdulzahra Makhrib, Abeer Jabbar Al-Rikabi i Emad Bakr Al-Zangana. "Represent the space PG(3, 8) by subspaces and sub-geometries". W INTERNATIONAL CONFERENCE OF COMPUTATIONAL METHODS IN SCIENCES AND ENGINEERING ICCMSE 2021. AIP Publishing, 2023. http://dx.doi.org/10.1063/5.0114859.
Pełny tekst źródłaChapron, Maxime, Christophe Blondeau, Michel Bergmann, Itham Salah el Din i Denis Sipp. "SCALABLE CLUSTERED ACTIVE SUBSPACES FOR KRIGING REGRESSION IN HIGH DIMENSION". W 15th International Conference on Evolutionary and Deterministic Methods for Design, Optimization and Control. Athens: Institute of Structural Analysis and Antiseismic Research National Technical University of Athens, 2023. http://dx.doi.org/10.7712/140123.10192.18902.
Pełny tekst źródłaRaporty organizacyjne na temat "Subspaces methods"
Harris, D. B. Characterizing source regions with signal subspace methods: Theory and computational methods. Office of Scientific and Technical Information (OSTI), grudzień 1989. http://dx.doi.org/10.2172/5041042.
Pełny tekst źródłaWang, Qiqi. Active Subspace Methods for Data-Intensive Inverse Problems. Office of Scientific and Technical Information (OSTI), kwiecień 2017. http://dx.doi.org/10.2172/1353429.
Pełny tekst źródłaConstantine, Paul. Active Subspace Methods for Data-Intensive Inverse Problems. Office of Scientific and Technical Information (OSTI), wrzesień 2019. http://dx.doi.org/10.2172/1566065.
Pełny tekst źródłaCarson, Erin, Nicholas Knight i James Demmel. Avoiding Communication in Two-Sided Krylov Subspace Methods. Fort Belvoir, VA: Defense Technical Information Center, sierpień 2011. http://dx.doi.org/10.21236/ada555879.
Pełny tekst źródłaMeza, Juan C., i W. W. Symes. Deflated Krylov Subspace Methods for Nearly Singular Linear Systems. Fort Belvoir, VA: Defense Technical Information Center, luty 1987. http://dx.doi.org/10.21236/ada455101.
Pełny tekst źródłaNeedell, Deanna, i Rachel Ward. Two-subspace Projection Method for Coherent Overdetermined Systems. Claremont Colleges Digital Library, 2012. http://dx.doi.org/10.5642/tspmcos.2012.01.
Pełny tekst źródłaBui-Thanh, Tan. Active Subspace Methods for Data-Intensive Inverse Problems (Final Report). Office of Scientific and Technical Information (OSTI), luty 2019. http://dx.doi.org/10.2172/1494035.
Pełny tekst źródłaLi, Zhilin, i Kazufumi Ito. Subspace Iteration and Immersed Interface Methods: Theory, Algorithm, and Applications. Fort Belvoir, VA: Defense Technical Information Center, sierpień 2010. http://dx.doi.org/10.21236/ada532686.
Pełny tekst źródłaElman, Howard C. Multigrid and Krylov Subspace Methods for the Discrete Stokes Equations. Fort Belvoir, VA: Defense Technical Information Center, czerwiec 1994. http://dx.doi.org/10.21236/ada598913.
Pełny tekst źródłaFreund, R. W., i N. M. Nachtigal. A new Krylov-subspace method for symmetric indefinite linear systems. Office of Scientific and Technical Information (OSTI), październik 1994. http://dx.doi.org/10.2172/10190810.
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