Learning in Graphical Models

Nonfiction, Computers, Advanced Computing, Artificial Intelligence, Science & Nature, Science, Physics, General Physics, General Computing
Cover of the book Learning in Graphical Models by , Springer Netherlands
View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart
Author: ISBN: 9789401150149
Publisher: Springer Netherlands Publication: December 6, 2012
Imprint: Springer Language: English
Author:
ISBN: 9789401150149
Publisher: Springer Netherlands
Publication: December 6, 2012
Imprint: Springer
Language: English

In the past decade, a number of different research communities within the computational sciences have studied learning in networks, starting from a number of different points of view. There has been substantial progress in these different communities and surprising convergence has developed between the formalisms. The awareness of this convergence and the growing interest of researchers in understanding the essential unity of the subject underlies the current volume.
Two research communities which have used graphical or network formalisms to particular advantage are the belief network community and the neural network community. Belief networks arose within computer science and statistics and were developed with an emphasis on prior knowledge and exact probabilistic calculations. Neural networks arose within electrical engineering, physics and neuroscience and have emphasised pattern recognition and systems modelling problems. This volume draws together researchers from these two communities and presents both kinds of networks as instances of a general unified graphical formalism. The book focuses on probabilistic methods for learning and inference in graphical models, algorithm analysis and design, theory and applications. Exact methods, sampling methods and variational methods are discussed in detail.
Audience: A wide cross-section of computationally oriented researchers, including computer scientists, statisticians, electrical engineers, physicists and neuroscientists.

View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

In the past decade, a number of different research communities within the computational sciences have studied learning in networks, starting from a number of different points of view. There has been substantial progress in these different communities and surprising convergence has developed between the formalisms. The awareness of this convergence and the growing interest of researchers in understanding the essential unity of the subject underlies the current volume.
Two research communities which have used graphical or network formalisms to particular advantage are the belief network community and the neural network community. Belief networks arose within computer science and statistics and were developed with an emphasis on prior knowledge and exact probabilistic calculations. Neural networks arose within electrical engineering, physics and neuroscience and have emphasised pattern recognition and systems modelling problems. This volume draws together researchers from these two communities and presents both kinds of networks as instances of a general unified graphical formalism. The book focuses on probabilistic methods for learning and inference in graphical models, algorithm analysis and design, theory and applications. Exact methods, sampling methods and variational methods are discussed in detail.
Audience: A wide cross-section of computationally oriented researchers, including computer scientists, statisticians, electrical engineers, physicists and neuroscientists.

More books from Springer Netherlands

Cover of the book Chemistry and Technology of Thermosetting Polymers in Construction Applications by
Cover of the book Renal Transplantation: Sense and Sensitization by
Cover of the book Vulnerability of Agriculture, Water and Fisheries to Climate Change by
Cover of the book The Rescue and Achievement of Refugee Scholars by
Cover of the book Clinical Application of Radiolabelled Platelets by
Cover of the book The Inclusion of Environmental Education in Science Teacher Education by
Cover of the book Cellular and Molecular Aspects of Plant-Nematode Interactions by
Cover of the book Environmental and Food Safety and Security for South-East Europe and Ukraine by
Cover of the book Solutions to Exercises in Intermediate Statistical Methods by
Cover of the book The Uses of Antiquity by
Cover of the book Molluscan Shellfish Safety by
Cover of the book Clean Technology and the Environment by
Cover of the book Social Capital as a Health Resource in Later Life: The Relevance of Context by
Cover of the book Landscapes and Landforms of Namibia by
Cover of the book Radiologic exploration of impotence by
We use our own "cookies" and third party cookies to improve services and to see statistical information. By using this website, you agree to our Privacy Policy