Tensor Factorization

Context-Aware Ranking with Factorization Models  eBooks & eLearning

Posted by alt_f4 at Sept. 27, 2015
Context-Aware Ranking with Factorization Models

Context-Aware Ranking with Factorization Models (Studies in Computational Intelligence) by Steffen Rendle
English | Nov. 11, 2010 | ISBN: 3642168973 | 183 Pages | PDF | 2 MB

Context-aware ranking is an important task with many applications. E.g. in recommender systems items (products, movies, …) and for search engines webpages should be ranked. In all these applications, the ranking is not global (i.e. always the same) but depends on the context.
Tensor Analysis and Elementary Differential Geometry for Physicists and Engineers (2nd edition)

Hung Nguyen-Schäfer, "Tensor Analysis and Elementary Differential Geometry for Physicists and Engineers (2nd edition)"
2016 | ISBN-10: 3662484951 | 396 pages | PDF | 4 MB

Introduction to Tensor Products of Banach Spaces  eBooks & eLearning

Posted by ChrisRedfield at Oct. 24, 2016
Introduction to Tensor Products of Banach Spaces

Raymond A. Ryan - Introduction to Tensor Products of Banach Spaces
Published: 2002-03-05 | ISBN: 1852334371, 1849968721 | PDF + DJVU | 239 pages | 36.3 MB

An Introduction to Tensor Calculus, Relativity and Cosmology (3rd Edition)  eBooks & eLearning

Posted by Jeembo at Oct. 20, 2016
An Introduction to Tensor Calculus, Relativity and Cosmology (3rd Edition)

An Introduction to Tensor Calculus, Relativity and Cosmology (3rd Edition) by Derek F. Lawden
English | 1982 | ISBN: 047110096X | 220 Pages | EPUB, MOBI, PDF | 204.2 MB

This elementary introduction pays special attention to aspects of tensor calculus and relativity that students tend to find most difficult.
Tensor Analysis and Elementary Differential Geometry for Physicists and Engineers, 2nd edition

Hung Nguyen-Schäfer and Jan-Philip Schmidt, "Tensor Analysis and Elementary Differential Geometry for Physicists and Engineers, 2nd edition"
English | ISBN: 3662484951 | 2016 | 396 pages | PDF | 4 MB

Tensor Analysis for Physicists, Second Edition  eBooks & eLearning

Posted by roxul at Sept. 18, 2016
Tensor Analysis for Physicists, Second Edition

J. A. Schouten, "Tensor Analysis for Physicists, Second Edition"
English | ISBN: 0486655822 | 1989 | 277 pages | Djvu | 8 MB

Quantum Group Symmetry and Q-Tensor Algebras  eBooks & eLearning

Posted by step778 at Sept. 5, 2016
Quantum Group Symmetry and Q-Tensor Algebras

L. C. Biedenharn, M. A. Lohe, "Quantum Group Symmetry and Q-Tensor Algebras"
1995 | pages: 303 | ISBN: 9810223315 | DJVU | 6 mb

Iterative Incomplete Factorization Methods  eBooks & eLearning

Posted by step778 at Aug. 25, 2016
Iterative Incomplete Factorization Methods

V.P. Il'in, "Iterative Incomplete Factorization Methods"
1992 | pages: 200 | ISBN: 9810209967 | DJVU | 2,3 mb

Signal and Image Processing for Remote Sensing, Second Edition  eBooks & eLearning

Posted by interes at April 24, 2015
Signal and Image Processing for Remote Sensing, Second Edition

Signal and Image Processing for Remote Sensing, Second Edition by C.H. Chen
English | 2012 | ISBN: 143985596X | 580 pages | PDF | 27,6 MB

Realtime Data Mining: Self-Learning Techniques for Recommendation Engines (repost)  eBooks & eLearning

Posted by ph4rr3l at March 14, 2014
Realtime Data Mining: Self-Learning Techniques for Recommendation Engines (repost)

Alexander Paprotny, Michael Thess, "Realtime Data Mining: Self-Learning Techniques for Recommendation Engines: Toward the Self-Learning Recommendation Engine"
English | ISBN: 3319013203 | 2013 | 297 pages | PDF | 4 MB

Describing novel mathematical concepts for recommendation engines, Realtime Data Mining: Self-Learning Techniques for Recommendation Engines features a sound mathematical framework unifying approaches based on control and learning theories, tensor factorization, and hierarchical methods. Furthermore, it presents promising results of numerous experiments on real-world data.​ The area of realtime data mining is currently developing at an exceptionally dynamic pace, and realtime data mining systems are the counterpart of today's “classic” data mining systems. Whereas the latter learn from historical data and then use it to deduce necessary actions, realtime analytics systems learn and act continuously and autonomously. In the vanguard of these new analytics systems are recommendation engines. They are principally found on the Internet, where all information is available in realtime and an immediate feedback is guaranteed.