Posted by **arundhati** at June 23, 2019

English | ISBN: 0821802631 | | 115 pages | PDF | 23 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 **arundhati** at Oct. 9, 2016

2016 | ISBN-10: 3319450255 | 208 pages | PDF | 6 MB

Posted by **ChrisRedfield** at Dec. 10, 2017

Published: 2014-01-10 | ISBN: 3319021311, 3319350250 | PDF | 384 pages | 4.04 MB

Posted by **AvaxGenius** at Aug. 13, 2019

English | PDF | 2005 | 574 Pages | ISBN : 3540259074 | 4.16 MB

Riemannian geometry is characterized, and research is oriented towards and shaped by concepts (geodesics, connections, curvature, …) and objectives, in particular to understand certain classes of (compact) Riemannian manifolds defined by curvature conditions (constant or positive or negative curvature, …). By way of contrast, geometric analysis is a perhaps somewhat less system- atic collection of techniques, for solving extremal problems naturally arising in geometry and for investigating and characterizing their solutions. It turns out that the two fields complement each other very well; geometric analysis offers tools for solving difficult problems in geometry, and Riemannian geom- etry stimulates progress in geometric analysis by setting ambitious goals.

Posted by **libr** at Oct. 29, 2017

English | 2014 | ISBN: 3319048031 | 140 pages | PDF | 1,9 MB

Posted by **Rare-1** at Oct. 26, 2016

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

Posted by **insetes** at Dec. 27, 2017

2014 | 116 Pages | ISBN: 3319086898 | PDF | 1 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.

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

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