Posted by **arundhati** at Sept. 12, 2017

2017 | ISBN-10: 1470425424 | 77 pages | PDF | 1 MB

Posted by **arundhati** at Aug. 7, 2017

1998 | ISBN-10: 1568814712 | 168 pages | PDF scan | 12 MB

Posted by **AvaxGenius** at July 21, 2017

English | PDF | 2016 | 216 Pages | ISBN : 3319450255 | 5.6 MB

This book presents a selection of the most recent algorithmic advances in Riemannian geometry in the context of machine learning, statistics, optimization, computer vision, and related fields. The unifying theme of the different chapters in the book is the exploitation of the geometry of data using the mathematical machinery of Riemannian geometry. As demonstrated by all the chapters in the book, when the data is intrinsically non-Euclidean, the utilization of this geometrical information can lead to better algorithms that can capture more accurately the structures inherent in the data, leading ultimately to better empirical performance.

Posted by **libr** at May 19, 2017

English | 2006-04-10 | ISBN: 0521619548, 0521853680 | PDF | 488 pages | 2.2 MB

Posted by **naag** at April 17, 2017

English | ISBN: 3319266527 | 2016 | 499 pages | EPUB | 1 MB

Posted by **Jeembo** at March 20, 2017

English | 2002 | ISBN: 3540431446 | 178 Pages | DJVU | 2.6 MB

The subject of this book is Osserman semi-Riemannian manifolds, and in particular, the Osserman conjecture in semi-Riemannian geometry.

Posted by **Jeembo** at March 20, 2017

English | 2001 | ISBN: 3540411089 | 504 Pages | DJVU | 5.7 MB

This book treats that part of Riemannian geometry related to more classical topics in a very original, clear and solid style.

Posted by **naag** at March 16, 2017

English | ISBN: 3319450255 | 2016 | PDF | 208 pages | 5.58 MB

Posted by **DZ123** at March 14, 2017

English | 2014 | ISBN: 3319086898 | PDF | pages: 112 | 1.4 mb

Posted by **leonardo78** at March 6, 2017

Publisher: Dover Publication | 2005 | ISBN: 0486442438 | 192 pages | DJVU | 2,9 MB

Non-Riemannian Geometry deals basically with manifolds dominated by the geometry of paths developed by the author, Luther Pfahler Eisenhart, and Oswald Veblen, who were faculty colleagues at Princeton University during the early twentieth century. Eisenhart played an active role in developing Princeton's preeminence among the world's centers for mathematical study, and he is equally renowned for his achievements as a researcher and an educator.