Books on the topic 'Dimensionality reduction'
Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles
Consult the top 50 books for your research on the topic 'Dimensionality reduction.'
Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.
You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.
Browse books on a wide variety of disciplines and organise your bibliography correctly.
Lee, John A., and Michel Verleysen, eds. Nonlinear Dimensionality Reduction. New York, NY: Springer New York, 2007. http://dx.doi.org/10.1007/978-0-387-39351-3.
Full textLespinats, Sylvain, Benoit Colange, and Denys Dutykh. Nonlinear Dimensionality Reduction Techniques. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-81026-9.
Full textGarzon, Max, Ching-Chi Yang, Deepak Venugopal, Nirman Kumar, Kalidas Jana, and Lih-Yuan Deng, eds. Dimensionality Reduction in Data Science. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-05371-9.
Full textPaul, Arati, and Nabendu Chaki. Dimensionality Reduction of Hyperspectral Imagery. Cham: Springer International Publishing, 2024. http://dx.doi.org/10.1007/978-3-031-42667-4.
Full textStrange, Harry, and Reyer Zwiggelaar. Open Problems in Spectral Dimensionality Reduction. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-03943-5.
Full textKramer, Oliver. Dimensionality Reduction with Unsupervised Nearest Neighbors. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-38652-7.
Full textKramer, Oliver. Dimensionality Reduction with Unsupervised Nearest Neighbors. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013.
Find full textShaw, Blake. Graph Embedding and Nonlinear Dimensionality Reduction. [New York, N.Y.?]: [publisher not identified], 2011.
Find full textGhojogh, Benyamin, Mark Crowley, Fakhri Karray, and Ali Ghodsi. Elements of Dimensionality Reduction and Manifold Learning. Cham: Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-10602-6.
Full textWang, Jianzhong. Geometric Structure of High-Dimensional Data and Dimensionality Reduction. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-27497-8.
Full textPopov, Valentin L., and Markus Heß. Method of Dimensionality Reduction in Contact Mechanics and Friction. Berlin, Heidelberg: Springer Berlin Heidelberg, 2015. http://dx.doi.org/10.1007/978-3-642-53876-6.
Full textservice), SpringerLink (Online, ed. Geometric Structure of High-Dimensional Data and Dimensionality Reduction. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011.
Find full textRos, Frederic, and Rabia Riad. Feature and Dimensionality Reduction for Clustering with Deep Learning. Cham: Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-48743-9.
Full textBarrett, Philip James. Exploratory database visualisation: The application & assessment of data and dimensionality reduction. Birmingham: Aston University. Department of Computer Science and Applied Mathematics, 1995.
Find full textFord, Gary E. Landsat D thematic mapper image dimensionality reduction and geometric correction accuracy: Final report. [Washington, DC: National Aeronautics and Space Administration, 1987.
Find full textGeometric data analysis: An empirical approach to dimensionality reduction and the study of patterns. New York: Wiley, 2001.
Find full textBacon, Simon. Machine learning for text classification of USENET newsgroups: A comparison of learning algorithms and dimensionality reduction techniques. [S.l: The Author], 1997.
Find full textNonlinear Dimensionality Reduction. Springer New York, 2010.
Find full textMultilabel Dimensionality Reduction. CRC Press, 2012.
Find full textYe, Jieping, Shuiwang Ji, and Liang Sun. Multi-Label Dimensionality Reduction. Taylor & Francis Group, 2016.
Find full textYe, Jieping, Shuiwang Ji, and Liang Sun. Multi-Label Dimensionality Reduction. Taylor & Francis Group, 2014.
Find full textYe, Jieping, Shuiwang Ji, and Liang Sun. Multi-Label Dimensionality Reduction. Taylor & Francis Group, 2016.
Find full textDimensionality Reduction in Data Science. Springer International Publishing AG, 2022.
Find full textStrange, Harry, and Reyer Zwiggelaar. Open Problems in Spectral Dimensionality Reduction. Springer, 2014.
Find full textStrange, Harry, and Reyer Zwiggelaar. Open Problems in Spectral Dimensionality Reduction. Springer London, Limited, 2014.
Find full textKramer, Oliver. Dimensionality Reduction with Unsupervised Nearest Neighbors. Springer, 2016.
Find full textKramer, Oliver. Dimensionality Reduction with Unsupervised Nearest Neighbors. Springer, 2013.
Find full textKrämer, Oliver. Dimensionality Reduction with Unsupervised Nearest Neighbors. Springer Berlin / Heidelberg, 2013.
Find full textNonlinear Dimensionality Reduction (Information Science and Statistics). Springer, 2007.
Find full textNonlinear Dimensionality Reduction (Information Science and Statistics). Springer, 2007.
Find full textGhojogh, Benyamin, Ali Ghodsi, Fakhri Karray, and Mark Crowley. Elements of Dimensionality Reduction and Manifold Learning. Springer International Publishing AG, 2022.
Find full textGeometric Structure of HighDimensional Data and Dimensionality Reduction. Springer, 2012.
Find full textLu, Haiping. Multilinear Subspace Learning: Dimensionality Reduction of Multidimensional Data. Taylor & Francis Group, 2013.
Find full textPlataniotis, Konstantinos N., Haiping Lu, and Anastasios Venetsanopoulos. Multilinear Subspace Learning: Dimensionality Reduction of Multidimensional Data. Taylor & Francis Group, 2013.
Find full textMultilinear Subspace Learning Dimensionality Reduction Of Multidimensional Data. CRC Press, 2013.
Find full textPlataniotis, Konstantinos N., Haiping Lu, and Anastasios Venetsanopoulos. Multilinear Subspace Learning: Dimensionality Reduction of Multidimensional Data. Taylor & Francis Group, 2013.
Find full textTripathy, B. K., Anveshrithaa S, and Shrusti Ghela. Unsupervised Learning Approaches for Dimensionality Reduction and Data Visualization. Taylor & Francis Group, 2021.
Find full textPopov, Valentin, and Markus Heß. Method of Dimensionality Reduction in Contact Mechanics and Friction. Springer Berlin / Heidelberg, 2016.
Find full textUnsupervised Learning Approaches for Dimensionality Reduction and Data Visualization. Taylor & Francis Group, 2021.
Find full textPopov, Valentin L., and Markus Heß. Method of Dimensionality Reduction in Contact Mechanics and Friction. Springer, 2014.
Find full textNonlinear Dimensionality Reduction Techniques: A Data Structure Preservation Approach. Springer International Publishing AG, 2022.
Find full textTripathy, B. K., Shrusti Ghela, and Anveshrithaa Sundareswaran. Unsupervised Learning Approaches for Dimensionality Reduction and Data Visualization. Taylor & Francis Group, 2021.
Find full textPopov, Valentin L., and Markus Heß. Method of Dimensionality Reduction in Contact Mechanics and Friction. Springer, 2014.
Find full textOja, Hannu, and Klaus Nordhausen. Linear Dimensionality Reduction: An Approach Based on Scatter Matrices. Wiley & Sons, Incorporated, John, 2022.
Find full textOja, Hannu, and Klaus Nordhausen. Linear Dimensionality Reduction: An Approach Based on Scatter Matrices. Wiley & Sons, Incorporated, John, 2022.
Find full textCarreira-Perpinan, Miguel A. Dimensionality Reduction (Chapman & Hall/Crc Computer Science & Data Analysis). Chapman & Hall/CRC, 2009.
Find full textOja, Hannu, and Klaus Nordhausen. Linear Dimensionality Reduction: An Approach Based on Scatter Matrices. Wiley & Sons, Limited, John, 2021.
Find full textTripathy, B. K., Shrusti Ghela, and Anveshrithaa Sundareswaran. Unsupervised Learning Approaches for Dimensionality Reduction and Data Visualization. Taylor & Francis Group, 2021.
Find full textDutykh, Denys, Sylvain Lespinats, and Benoit Colange. Nonlinear Dimensionality Reduction Techniques: A Data Structure Preservation Approach. Springer International Publishing AG, 2021.
Find full textTripathy, B. K., Anveshrithaa S, and Shrusti Ghela. Unsupervised Learning Approaches for Dimensionality Reduction and Data Visualization. Taylor & Francis Group, 2021.
Find full text