Linear algebra and optimization with applications to machine learning. (Record no. 72583)
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| 000 -LEADER | |
|---|---|
| fixed length control field | 03563cam a2200445Ma 4500 |
| 001 - CONTROL NUMBER | |
| control field | 00011446 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
| fixed length control field | 200308s2020 si a ob 001 0 eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| ISBN | 9789811206405 |
| -- | (ebook) |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| ISBN | 9811206406 |
| -- | (ebook) |
| 082 04 - CLASSIFICATION NUMBER | |
| Call Number | 512.50285 |
| 100 1# - AUTHOR NAME | |
| Author | Gallier, Jean H. |
| 245 10 - TITLE STATEMENT | |
| Title | Linear algebra and optimization with applications to machine learning. |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT) | |
| Place of publication | Singapore : |
| Publisher | World Scientific Publishing Co. Pte. Ltd., |
| Year of publication | c2020. |
| 300 ## - PHYSICAL DESCRIPTION | |
| Number of Pages | 1 online resource (824 p.) |
| 505 0# - FORMATTED CONTENTS NOTE | |
| Remark 2 | ch. 1. Introduction -- ch. 2. Vector spaces, bases, linear maps -- ch. 3. Matrices and linear maps -- ch. 4. Haar bases, haar wavelets, hadamard matrices -- ch. 5. Direct sums, rank-nullity theorem, affine maps -- ch. 6. Determinants -- ch. 7. Gaussian elimination, LU-factorization, Cholesky factorization, reduced row echelon form -- ch. 8. Vector norms and matrix norms -- ch. 9. Iterative methods for solving linear systems -- ch. 10. The dual space and duality -- ch. 11. Euclidean spaces -- ch. 12. QR-decomposition for arbitrary matrices -- ch. 13. Hermitian spaces -- ch. 14. Eigenvectors and eigenvalues -- ch. 15. Unit quaternions and rotations in SO(3) -- ch. 16. Spectral theorems in euclidean and hermitian spaces -- ch. 17. Computing eigenvalues and eigenvectors -- ch. 18. Graphs and graph laplacians; basic facts -- ch. 19. Spectral graph drawing -- ch. 20. Singular value decomposition and polar form -- ch. 21. Applications of SVD and pseudo-inverses -- ch. 22. Annihilating polynomials and the primary decomposition -- Bibliography -- Index. |
| 520 ## - SUMMARY, ETC. | |
| Summary, etc | "This book provides the mathematical fundamentals of linear algebra to practicers in computer vision, machine learning, robotics, applied mathematics, and electrical engineering. By only assuming a knowledge of calculus, the authors develop, in a rigorous yet down to earth manner, the mathematical theory behind concepts such as: vectors spaces, bases, linear maps, duality, Hermitian spaces, the spectral theorems, SVD, and the primary decomposition theorem. At all times, pertinent real-world applications are provided. This book includes the mathematical explanations for the tools used which we believe that is adequate for computer scientists, engineers and mathematicians who really want to do serious research and make significant contributions in their respective fields"--Publisher's website. |
| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| General subdivision | Data processing. |
| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| General subdivision | Mathematics. |
| 700 1# - AUTHOR 2 | |
| Author 2 | Quaintance, Jocelyn. |
| 856 40 - ELECTRONIC LOCATION AND ACCESS | |
| Uniform Resource Identifier | https://www.worldscientific.com/worldscibooks/10.1142/11446#t=toc |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
| Koha item type | eBooks |
| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Algebras, Linear |
| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Computer science |
| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Computer-aided design. |
| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Robotics. |
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