Libros sobre el tema "Dimensionality reduction"

Lee, John A. y Michel Verleysen, eds. Nonlinear Dimensionality Reduction. New York, NY: Springer New York, 2007. http://dx.doi.org/10.1007/978-0-387-39351-3.

Lespinats, Sylvain, Benoit Colange y Denys Dutykh. Nonlinear Dimensionality Reduction Techniques. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-81026-9.

Garzon, Max, Ching-Chi Yang, Deepak Venugopal, Nirman Kumar, Kalidas Jana y 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.

Paul, Arati y Nabendu Chaki. Dimensionality Reduction of Hyperspectral Imagery. Cham: Springer International Publishing, 2024. http://dx.doi.org/10.1007/978-3-031-42667-4.

Strange, Harry y Reyer Zwiggelaar. Open Problems in Spectral Dimensionality Reduction. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-03943-5.

Kramer, Oliver. Dimensionality Reduction with Unsupervised Nearest Neighbors. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-38652-7.

Kramer, Oliver. Dimensionality Reduction with Unsupervised Nearest Neighbors. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013.

Shaw, Blake. Graph Embedding and Nonlinear Dimensionality Reduction. [New York, N.Y.?]: [publisher not identified], 2011.

Ghojogh, Benyamin, Mark Crowley, Fakhri Karray y 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.

Wang, 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.

Popov, Valentin L. y 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.

service), SpringerLink (Online, ed. Geometric Structure of High-Dimensional Data and Dimensionality Reduction. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011.

Ros, Frederic y 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.

Barrett, Philip James. Exploratory database visualisation: The application & assessment of data and dimensionality reduction. Birmingham: Aston University. Department of Computer Science and Applied Mathematics, 1995.

Ford, Gary E. Landsat D thematic mapper image dimensionality reduction and geometric correction accuracy: Final report. [Washington, DC: National Aeronautics and Space Administration, 1987.

Geometric data analysis: An empirical approach to dimensionality reduction and the study of patterns. New York: Wiley, 2001.

Bacon, Simon. Machine learning for text classification of USENET newsgroups: A comparison of learning algorithms and dimensionality reduction techniques. [S.l: The Author], 1997.

Nonlinear Dimensionality Reduction. Springer New York, 2010.

Multilabel Dimensionality Reduction. CRC Press, 2012.

Ye, Jieping, Shuiwang Ji y Liang Sun. Multi-Label Dimensionality Reduction. Taylor & Francis Group, 2016.

Ye, Jieping, Shuiwang Ji y Liang Sun. Multi-Label Dimensionality Reduction. Taylor & Francis Group, 2014.

Ye, Jieping, Shuiwang Ji y Liang Sun. Multi-Label Dimensionality Reduction. Taylor & Francis Group, 2016.

Dimensionality Reduction in Data Science. Springer International Publishing AG, 2022.

Strange, Harry y Reyer Zwiggelaar. Open Problems in Spectral Dimensionality Reduction. Springer, 2014.

Strange, Harry y Reyer Zwiggelaar. Open Problems in Spectral Dimensionality Reduction. Springer London, Limited, 2014.

Kramer, Oliver. Dimensionality Reduction with Unsupervised Nearest Neighbors. Springer, 2016.

Kramer, Oliver. Dimensionality Reduction with Unsupervised Nearest Neighbors. Springer, 2013.

Krämer, Oliver. Dimensionality Reduction with Unsupervised Nearest Neighbors. Springer Berlin / Heidelberg, 2013.

Nonlinear Dimensionality Reduction (Information Science and Statistics). Springer, 2007.

Nonlinear Dimensionality Reduction (Information Science and Statistics). Springer, 2007.

Ghojogh, Benyamin, Ali Ghodsi, Fakhri Karray y Mark Crowley. Elements of Dimensionality Reduction and Manifold Learning. Springer International Publishing AG, 2022.

Geometric Structure of HighDimensional Data and Dimensionality Reduction. Springer, 2012.

Lu, Haiping. Multilinear Subspace Learning: Dimensionality Reduction of Multidimensional Data. Taylor & Francis Group, 2013.

Plataniotis, Konstantinos N., Haiping Lu y Anastasios Venetsanopoulos. Multilinear Subspace Learning: Dimensionality Reduction of Multidimensional Data. Taylor & Francis Group, 2013.

Multilinear Subspace Learning Dimensionality Reduction Of Multidimensional Data. CRC Press, 2013.

Plataniotis, Konstantinos N., Haiping Lu y Anastasios Venetsanopoulos. Multilinear Subspace Learning: Dimensionality Reduction of Multidimensional Data. Taylor & Francis Group, 2013.

Tripathy, B. K., Anveshrithaa S y Shrusti Ghela. Unsupervised Learning Approaches for Dimensionality Reduction and Data Visualization. Taylor & Francis Group, 2021.

Popov, Valentin y Markus Heß. Method of Dimensionality Reduction in Contact Mechanics and Friction. Springer Berlin / Heidelberg, 2016.

Unsupervised Learning Approaches for Dimensionality Reduction and Data Visualization. Taylor & Francis Group, 2021.

Popov, Valentin L. y Markus Heß. Method of Dimensionality Reduction in Contact Mechanics and Friction. Springer, 2014.

Nonlinear Dimensionality Reduction Techniques: A Data Structure Preservation Approach. Springer International Publishing AG, 2022.

Tripathy, B. K., Shrusti Ghela y Anveshrithaa Sundareswaran. Unsupervised Learning Approaches for Dimensionality Reduction and Data Visualization. Taylor & Francis Group, 2021.

Popov, Valentin L. y Markus Heß. Method of Dimensionality Reduction in Contact Mechanics and Friction. Springer, 2014.

Oja, Hannu y Klaus Nordhausen. Linear Dimensionality Reduction: An Approach Based on Scatter Matrices. Wiley & Sons, Incorporated, John, 2022.

Oja, Hannu y Klaus Nordhausen. Linear Dimensionality Reduction: An Approach Based on Scatter Matrices. Wiley & Sons, Incorporated, John, 2022.

Carreira-Perpinan, Miguel A. Dimensionality Reduction (Chapman & Hall/Crc Computer Science & Data Analysis). Chapman & Hall/CRC, 2009.

Oja, Hannu y Klaus Nordhausen. Linear Dimensionality Reduction: An Approach Based on Scatter Matrices. Wiley & Sons, Limited, John, 2021.

Tripathy, B. K., Shrusti Ghela y Anveshrithaa Sundareswaran. Unsupervised Learning Approaches for Dimensionality Reduction and Data Visualization. Taylor & Francis Group, 2021.

Dutykh, Denys, Sylvain Lespinats y Benoit Colange. Nonlinear Dimensionality Reduction Techniques: A Data Structure Preservation Approach. Springer International Publishing AG, 2021.

Tripathy, B. K., Anveshrithaa S y Shrusti Ghela. Unsupervised Learning Approaches for Dimensionality Reduction and Data Visualization. Taylor & Francis Group, 2021.