Gotowa bibliografia na temat „Data approximation”
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Artykuły w czasopismach na temat "Data approximation"
FROYLAND, GARY, KEVIN JUDD, ALISTAIR I. MEES, DAVID WATSON i KENJI MURAO. "CONSTRUCTING INVARIANT MEASURES FROM DATA". International Journal of Bifurcation and Chaos 05, nr 04 (sierpień 1995): 1181–92. http://dx.doi.org/10.1142/s0218127495000843.
Pełny tekst źródłaGrubas, Serafim I., Georgy N. Loginov i Anton A. Duchkov. "Traveltime-table compression using artificial neural networks for Kirchhoff-migration processing of microseismic data". GEOPHYSICS 85, nr 5 (19.08.2020): U121—U128. http://dx.doi.org/10.1190/geo2019-0427.1.
Pełny tekst źródłaSTOJANOVIĆ, MIRJANA. "PERTURBED SCHRÖDINGER EQUATION WITH SINGULAR POTENTIAL AND INITIAL DATA". Communications in Contemporary Mathematics 08, nr 04 (sierpień 2006): 433–52. http://dx.doi.org/10.1142/s0219199706002180.
Pełny tekst źródłaFRAHLING, GEREON, PIOTR INDYK i CHRISTIAN SOHLER. "SAMPLING IN DYNAMIC DATA STREAMS AND APPLICATIONS". International Journal of Computational Geometry & Applications 18, nr 01n02 (kwiecień 2008): 3–28. http://dx.doi.org/10.1142/s0218195908002520.
Pełny tekst źródłaChen, Jing-Bo, Hong Liu i Zhi-Fu Zhang. "A separable-kernel decomposition method for approximating the DSR continuation operator". GEOPHYSICS 72, nr 1 (styczeń 2007): S25—S31. http://dx.doi.org/10.1190/1.2399368.
Pełny tekst źródłaMardia, K. V., i I. L. Dryden. "Shape distributions for landmark data". Advances in Applied Probability 21, nr 4 (grudzień 1989): 742–55. http://dx.doi.org/10.2307/1427764.
Pełny tekst źródłaMardia, K. V., i I. L. Dryden. "Shape distributions for landmark data". Advances in Applied Probability 21, nr 04 (grudzień 1989): 742–55. http://dx.doi.org/10.1017/s0001867800019029.
Pełny tekst źródłaBirch, A. C., i A. G. Kosovichev. "Towards a Wave Theory Interpretation of Time-Distance Helioseismology Data". Symposium - International Astronomical Union 203 (2001): 180–82. http://dx.doi.org/10.1017/s0074180900219025.
Pełny tekst źródłaDong, Bin, Zuowei Shen i Jianbin Yang. "Approximation from Noisy Data". SIAM Journal on Numerical Analysis 59, nr 5 (styczeń 2021): 2722–45. http://dx.doi.org/10.1137/20m1389091.
Pełny tekst źródłaPiegl, L. A., i W. Tiller. "Data Approximation Using Biarcs". Engineering with Computers 18, nr 1 (29.04.2002): 59–65. http://dx.doi.org/10.1007/s003660200005.
Pełny tekst źródłaRozprawy doktorskie na temat "Data approximation"
Ross, Colin. "Applications of data fusion in data approximation". Thesis, University of Huddersfield, 2002. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.247372.
Pełny tekst źródłaDeligiannakis, Antonios. "Accurate data approximation in constrained environments". College Park, Md. : University of Maryland, 2005. http://hdl.handle.net/1903/2681.
Pełny tekst źródłaThesis research directed by: Computer Science. Title from abstract of PDF. Includes bibliographical references. Published by UMI Dissertation Services, Ann Arbor, Mich. Also available in paper.
Tomek, Peter. "Approximation of Terrain Data Utilizing Splines". Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2012. http://www.nusl.cz/ntk/nusl-236488.
Pełny tekst źródłaCao, Phuong Thao. "Approximation of OLAP queries on data warehouses". Phd thesis, Université Paris Sud - Paris XI, 2013. http://tel.archives-ouvertes.fr/tel-00905292.
Pełny tekst źródłaLehman, Eric (Eric Allen) 1970. "Approximation algorithms for grammar-based data compression". Thesis, Massachusetts Institute of Technology, 2002. http://hdl.handle.net/1721.1/87172.
Pełny tekst źródłaIncludes bibliographical references (p. 109-113).
This thesis considers the smallest grammar problem: find the smallest context-free grammar that generates exactly one given string. We show that this problem is intractable, and so our objective is to find approximation algorithms. This simple question is connected to many areas of research. Most importantly, there is a link to data compression; instead of storing a long string, one can store a small grammar that generates it. A small grammar for a string also naturally brings out underlying patterns, a fact that is useful, for example, in DNA analysis. Moreover, the size of the smallest context-free grammar generating a string can be regarded as a computable relaxation of Kolmogorov complexity. Finally, work on the smallest grammar problem qualitatively extends the study of approximation algorithms to hierarchically-structured objects. In this thesis, we establish hardness results, evaluate several previously proposed algorithms, and then present new procedures with much stronger approximation guarantees.
by Eric Lehman.
Ph.D.
Hou, Jun. "Function Approximation and Classification with Perturbed Data". The Ohio State University, 2021. http://rave.ohiolink.edu/etdc/view?acc_num=osu1618266875924225.
Pełny tekst źródłaZaman, Muhammad Adib Uz. "Bicubic L1 Spline Fits for 3D Data Approximation". Thesis, Northern Illinois University, 2018. http://pqdtopen.proquest.com/#viewpdf?dispub=10751900.
Pełny tekst źródłaUnivariate cubic L1 spline fits have been successful to preserve the shapes of 2D data with abrupt changes. The reason is that the minimization of L1 norm of the data is considered, as opposite to L2 norm. While univariate L1 spline fits for 2D data are discussed by many, bivariate L1 spline fits for 3D data are yet to be fully explored. This thesis aims to develop bicubic L1 spline fits for 3D data approximation. This can be achieved by solving a bi-level optimization problem. One level is bivariate cubic spline interpolation and the other level is L1 error minimization. In the first level, a bicubic interpolated spline surface will be constructed on a rectangular grid with necessary first and second order derivative values estimated by using a 5-point window algorithm for univariate L 1 interpolation. In the second level, the absolute error (i.e. L1 norm) will be minimized using an iterative gradient search. This study may be extended to higher dimensional cubic L 1 spline fits research.
Cooper, Philip. "Rational approximation of discrete data with asymptotic behaviour". Thesis, University of Huddersfield, 2007. http://eprints.hud.ac.uk/id/eprint/2026/.
Pełny tekst źródłaSchmid, Dominik. "Scattered data approximation on the rotation group and generalizations". Aachen Shaker, 2009. http://d-nb.info/995021562/04.
Pełny tekst źródłaMcQuarrie, Shane Alexander. "Data Assimilation in the Boussinesq Approximation for Mantle Convection". BYU ScholarsArchive, 2018. https://scholarsarchive.byu.edu/etd/6951.
Pełny tekst źródłaKsiążki na temat "Data approximation"
Iske, Armin. Approximation Theory and Algorithms for Data Analysis. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-05228-7.
Pełny tekst źródłaMotwani, Rajeev. Lecture notes on approximation algorithms. Stanford, CA: Dept. of Computer Science, Stanford University, 1992.
Znajdź pełny tekst źródłaC, Mason J., i Cox M. G, red. Algorithms for approximation II: Based on the proceedings of the Second International Conference on Algorithms for Approximation, held at Royal Military College of Science, Shrivenham, July 1988. London: Chapman and Hall, 1990.
Znajdź pełny tekst źródłaFranke, Richard. Recent advances in the approximation of surfaces from scattered data. Monterey, Calif: Naval Postgraduate School, 1987.
Znajdź pełny tekst źródłaIvanov, Viktor Vladimirovich. Metody vychisleniĭ na ĖVM: Spravochnoe posobie. Kiev: Nauk. dumka, 1986.
Znajdź pełny tekst źródłaFranke, Richard H. Least squares surface approximation to scattered data using multiquadric functions. Monterey, Calif: Naval Postgraduate School, 1993.
Znajdź pełny tekst źródłaMolchanov, I. N. Mashinnye metody reshenii͡a︡ prikladnykh zadach algebra, priblizhenie funkt͡s︡iĭ. Kiev: Nauk. dumka, 1987.
Znajdź pełny tekst źródłaK, Ray Bimal, red. Polygonal approximation and scale-space analysis. Oakville, Ont: Apple Academic Press, 2013.
Znajdź pełny tekst źródłaC, Mason J., Cox M. G i Institute of Mathematics and Its Applications., red. Algorithms for approximation: Based on the proceedings of the IMA Conference on Algorithms for the Approximation of Functions and Data, held at the Royal Military College of Science, Shrivenham, July 1985. Oxford [Oxfordshire]: Clarendon Press, 1987.
Znajdź pełny tekst źródłaEitan, Tadmor, Institute for Computer Applications in Science and Engineering. i Langley Research Center, red. Recovering pointwise values of discontinuous data within spectral accuracy. Hampton, Va: Institute for Computer Applications in Science and Engineering, NASA Langley Research Center, 1985.
Znajdź pełny tekst źródłaCzęści książek na temat "Data approximation"
Shekhar, Shashi, i Hui Xiong. "Data Approximation". W Encyclopedia of GIS, 203. Boston, MA: Springer US, 2008. http://dx.doi.org/10.1007/978-0-387-35973-1_237.
Pełny tekst źródłaHutchings, Matthew, i Bertrand Gauthier. "Local Optimisation of Nyström Samples Through Stochastic Gradient Descent". W Machine Learning, Optimization, and Data Science, 123–40. Cham: Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-25599-1_10.
Pełny tekst źródłaMarkovsky, Ivan. "From Data to Models". W Low-Rank Approximation, 37–70. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-89620-5_2.
Pełny tekst źródłaDeng, Shaobo, Huihui Lu, Sujie Guan, Min Li i Hui Wang. "Approximation Relation for Rough Sets". W Data Mining and Big Data, 402–17. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-7502-7_38.
Pełny tekst źródłaRengaswamy, Raghunathan, i Resmi Suresh. "Function Approximation Methods". W Data Science for Engineers, 175–252. Boca Raton: CRC Press, 2022. http://dx.doi.org/10.1201/b23276-6.
Pełny tekst źródłaIske, Armin. "Euclidean Approximation". W Approximation Theory and Algorithms for Data Analysis, 103–38. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-05228-7_4.
Pełny tekst źródłaIske, Armin. "Chebyshev Approximation". W Approximation Theory and Algorithms for Data Analysis, 139–84. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-05228-7_5.
Pełny tekst źródłaMarkovsky, Ivan. "Data-Driven Filtering and Control". W Low-Rank Approximation, 161–72. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-89620-5_6.
Pełny tekst źródłaAdir, Allon, Ehud Aharoni, Nir Drucker, Ronen Levy, Hayim Shaul i Omri Soceanu. "Approximation Methods Part II: Approximations of Standard Functions". W Homomorphic Encryption for Data Science (HE4DS), 125–47. Cham: Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-65494-7_6.
Pełny tekst źródłaWu, Weili, Yi Li, Panos M. Pardalos i Ding-Zhu Du. "Data-Dependent Approximation in Social Computing". W Approximation and Optimization, 27–34. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-12767-1_3.
Pełny tekst źródłaStreszczenia konferencji na temat "Data approximation"
Ma, Guanqun, David Lenz, Tom Peterka, Hanqi Guo i Bei Wang. "Critical Point Extraction from Multivariate Functional Approximation". W 2024 IEEE Topological Data Analysis and Visualization (TopoInVis), 12–22. IEEE, 2024. http://dx.doi.org/10.1109/topoinvis64104.2024.00006.
Pełny tekst źródłaSahrom, Nor Ashikin, Mohammad Izat Emir Zulkifly i Siti Nur Idara Rosli. "Interval-Valued Fuzzy Bézier Surface Approximation". W 2024 5th International Conference on Artificial Intelligence and Data Sciences (AiDAS), 1–5. IEEE, 2024. http://dx.doi.org/10.1109/aidas63860.2024.10730727.
Pełny tekst źródłaBarbas, Petros, Aristidis G. Vrahatis i Sotiris K. Tasoulis. "RLAC: Random Line Approximation Clustering". W 2021 IEEE International Conference on Big Data (Big Data). IEEE, 2021. http://dx.doi.org/10.1109/bigdata52589.2021.9671596.
Pełny tekst źródłaZhao, Danfeng, Zhou Huang, Feng Zhou, Antonio Liotta i Dongmei Huang. "An Approximation Method for Large Graph Similarity". W 2020 IEEE International Conference on Big Data (Big Data). IEEE, 2020. http://dx.doi.org/10.1109/bigdata50022.2020.9378447.
Pełny tekst źródłaDas, Abhinandan, Johannes Gehrke i Mirek Riedewald. "Approximation techniques for spatial data". W the 2004 ACM SIGMOD international conference. New York, New York, USA: ACM Press, 2004. http://dx.doi.org/10.1145/1007568.1007646.
Pełny tekst źródłaFreedman, Daniel, i Pavel Kisilev. "Fast Data Reduction via KDE Approximation". W 2009 Data Compression Conference (DCC). IEEE, 2009. http://dx.doi.org/10.1109/dcc.2009.47.
Pełny tekst źródłaPanda, Biswanath, Mirek Riedewald, Johannes Gehrke i Stephen B. Pope. "High-Speed Function Approximation". W Seventh IEEE International Conference on Data Mining (ICDM 2007). IEEE, 2007. http://dx.doi.org/10.1109/icdm.2007.107.
Pełny tekst źródłaHuang, Zhou, i Feng Zhou. "An Approximation Method for Querying Similar Large Graphs". W 2022 IEEE International Conference on Big Data (Big Data). IEEE, 2022. http://dx.doi.org/10.1109/bigdata55660.2022.10020310.
Pełny tekst źródłaShahcheraghi, Maryam, Trevor Cappon, Samet Oymak, Evangelos Papalexakis, Eamonn Keogh, Zachary Zimmerman i Philip Brisk. "Matrix Profile Index Approximation for Streaming Time Series". W 2021 IEEE International Conference on Big Data (Big Data). IEEE, 2021. http://dx.doi.org/10.1109/bigdata52589.2021.9671484.
Pełny tekst źródłaKannan, Ramakrishnan, Mariya Ishteva i Haesun Park. "Bounded Matrix Low Rank Approximation". W 2012 IEEE 12th International Conference on Data Mining (ICDM). IEEE, 2012. http://dx.doi.org/10.1109/icdm.2012.131.
Pełny tekst źródłaRaporty organizacyjne na temat "Data approximation"
Franke, Richard, Hans Hagen i Gregory M. Nielson. Least Squares Surface Approximation to Scattered Data Using Multiquadric Functions. Fort Belvoir, VA: Defense Technical Information Center, grudzień 1992. http://dx.doi.org/10.21236/ada259804.
Pełny tekst źródłaRay, Jaideep, Matthew Barone, Stefan Domino, Tania Banerjee i Sanjay Ranka. Verification of Data-Driven Models of Physical Phenomena using Interpretable Approximation. Office of Scientific and Technical Information (OSTI), wrzesień 2021. http://dx.doi.org/10.2172/1821318.
Pełny tekst źródłaBaraniuk, Richard, Ronald DeVore, Sanjeev Kulkarni, Andrew Kurdila, Stanley Osher, Guergana Petrova, Robert Sharpley, Richard Tsai i Hongkai Zhao. Model Classes, Approximation, and Metrics for Dynamic Processing of Urban Terrain Data. Fort Belvoir, VA: Defense Technical Information Center, styczeń 2013. http://dx.doi.org/10.21236/ada586168.
Pełny tekst źródłaFranke, Richard. Using Legendre Functions for Spatial Covariance Approximation and Investigation of Radial Nonisotrophy for NOGAPS Data. Fort Belvoir, VA: Defense Technical Information Center, styczeń 2001. http://dx.doi.org/10.21236/ada389396.
Pełny tekst źródłaWu, Yan, Sonia Fahmy i Ness B. Shroff. On the Construction of a Maximum-Lifetime Data Gathering Tree in Sensor Networks: NP-Completeness and Approximation Algorithm. Fort Belvoir, VA: Defense Technical Information Center, styczeń 2008. http://dx.doi.org/10.21236/ada517885.
Pełny tekst źródłaShah, Rajiv R. High-Level Adaptive Signal Processing Architecture with Applications to Radar Non-Gaussian Clutter. Volume 2. A New Technique for Distribution Approximation of Random Data. Fort Belvoir, VA: Defense Technical Information Center, wrzesień 1995. http://dx.doi.org/10.21236/ada300902.
Pełny tekst źródłaGorton, O., i J. Escher. Cross Sections for Neutron-Induced Reactions from Surrogate Data: Assessing the Use of the Weisskopf-Ewing Approximation for (n,n') and (n,2n) Reactions. Office of Scientific and Technical Information (OSTI), wrzesień 2020. http://dx.doi.org/10.2172/1668500.
Pełny tekst źródłaGuan, Jiajing, Sophia Bragdon i Jay Clausen. Predicting soil moisture content using Physics-Informed Neural Networks (PINNs). Engineer Research and Development Center (U.S.), sierpień 2024. http://dx.doi.org/10.21079/11681/48794.
Pełny tekst źródłaBunn, M. I., T. R. Carter, H. A. J. Russell i C. E. Logan. A semiquantitative representation of uncertainty for the 3D Paleozoic bedrock model of Southern Ontario. Natural Resources Canada/CMSS/Information Management, 2023. http://dx.doi.org/10.4095/331658.
Pełny tekst źródłaRofman, Rafael, Joaquín Baliña i Emanuel López. Evaluating the Impact of COVID-19 on Pension Systems in Latin America and the Caribbean. The Case of Argentina. Inter-American Development Bank, październik 2022. http://dx.doi.org/10.18235/0004508.
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