Posted by **AvaxGenius** at June 24, 2017

English | PDF | 2017 | 278 Pages | ISBN : 3319568280 | 6.84 MB

This valuable source for graduate students and researchers provides a comprehensive introduction to current theories and applications in optimization methods and network models. Contributions to this book are focused on new efficient algorithms and rigorous mathematical theories, which can be used to optimize and analyze mathematical graph structures with massive size and high density induced by natural or artificial complex networks.

Posted by **tanas.olesya** at June 23, 2017

English | 23 Dec. 2014 | ISBN: 3319149733 | 316 Pages | PDF | 6MB

The workshop covered a diverse range of topics on algorithms and discrete mathematics, including computational geometry, algorithms including approximation algorithms, graph theory and computational complexity.

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

English | PDF | 2012 | 81 Pages | ISBN : 1447129776 | 3.2 MB

Entropy Guided Transformation Learning: Algorithms and Applications (ETL) presents a machine learning algorithm for classification tasks. ETL generalizes Transformation Based Learning (TBL) by solving the TBL bottleneck: the construction of good template sets. ETL automatically generates templates using Decision Tree decomposition.

Posted by **roxul** at June 21, 2017

2007 | ISBN: 0898716233 | 466 pages | PDF | 5,7 MB

Posted by **Underaglassmoon** at June 19, 2017

Wiley | English | August 2017 | ISBN-10: 1119259762 | 416 pages | PDF | 12.13 mb

by Jouni Smed (Author), Harri Hakonen (Author)

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

English | 2015 | ASIN: B017XXKPNS | 6 pages | PDF + EPUB | 0.5 Mb

Posted by **hill0** at June 16, 2017

English | 1 July 2017 | ISBN: 3319446827 | 363 Pages | PDF | 13.62 MB

This book presents contributions on topics ranging from novel applications of topological analysis for particular problems, through studies of the effectiveness of modern topological methods, algorithmic improvements on existing methods,

Posted by **libr** at June 10, 2017

English | 2014 | ISBN: 1107044367 | 320 pages | PDF | 13,4 MB

Posted by **roxul** at June 9, 2017

English | ISBN: 3319492616 | 2017 | 372 pages | PDF | 17 MB

Posted by **naag** at June 7, 2017

MP4 | Video: AVC 1280x720 | Audio: AAC 44KHz 2ch | Duration: 1 Hours 15M | 405 MB

Machine learning is the subfield of computer science that gives computers the ability to learn without being explicitly programmed. It explores the study and construction of algorithms that can learn from and make predictions on data. The R language is widely used among statisticians and data miners to develop statistical software and data analysis.