Beschreibung
The book explores connections between Riemannian geometry and several well known machine learning techniques, including boosting and logistic regression. In addition to providing motivation for these techniques, the book provides a mechanism for designing new statistical procedures that are shown experimentally to outperform the state-of-the-art. This work follows up on traditional information geometry with a more applied machine learning perspective.
Autorenporträt
Guy Lebanon is a senior manager at LinkedIn, where he leads the feed relevance team. Prior to that he was a senior manager at Amazon where he lead the machine learning science team at Amazon's main campus in Seattle WA and before that he was a tenured professor at the Georgia Institute of Technology. His main area of research is machine learning.
Herstellerkennzeichnung:
OmniScriptum SRL
Str. Armeneasca 28/1, office 1
2012 Chisinau
MD
E-Mail: info@omniscriptum.com
