logo

EbookBell.com

Most ebook files are in PDF format, so you can easily read them using various software such as Foxit Reader or directly on the Google Chrome browser.
Some ebook files are released by publishers in other formats such as .awz, .mobi, .epub, .fb2, etc. You may need to install specific software to read these formats on mobile/PC, such as Calibre.

Please read the tutorial at this link:  https://ebookbell.com/faq 


We offer FREE conversion to the popular formats you request; however, this may take some time. Therefore, right after payment, please email us, and we will try to provide the service as quickly as possible.


For some exceptional file formats or broken links (if any), please refrain from opening any disputes. Instead, email us first, and we will try to assist within a maximum of 6 hours.

EbookBell Team

Topics In Grammatical Inference 1st Edition Jeffrey Heinz Jos M Sempere Eds

  • SKU: BELL-5485530
Topics In Grammatical Inference 1st Edition Jeffrey Heinz Jos M Sempere Eds
$ 31.00 $ 45.00 (-31%)

4.4

72 reviews

Topics In Grammatical Inference 1st Edition Jeffrey Heinz Jos M Sempere Eds instant download after payment.

Publisher: Springer-Verlag Berlin Heidelberg
File Extension: PDF
File size: 4.98 MB
Pages: 258
Author: Jeffrey Heinz, José M. Sempere (eds.)
ISBN: 9783662483930, 9783662483954, 3662483939, 3662483955
Language: English
Year: 2016
Edition: 1

Product desciption

Topics In Grammatical Inference 1st Edition Jeffrey Heinz Jos M Sempere Eds by Jeffrey Heinz, José M. Sempere (eds.) 9783662483930, 9783662483954, 3662483939, 3662483955 instant download after payment.

This book explains advanced theoretical and application-related issues in grammatical inference, a research area inside the inductive inference paradigm for machine learning. The first three chapters of the book deal with issues regarding theoretical learning frameworks; the next four chapters focus on the main classes of formal languages according to Chomsky's hierarchy, in particular regular and context-free languages; and the final chapter addresses the processing of biosequences.

The topics chosen are of foundational interest with relatively mature and established results, algorithms and conclusions. The book will be of value to researchers and graduate students in areas such as theoretical computer science, machine learning, computational linguistics, bioinformatics, and cognitive psychology who are engaged with the study of learning, especially of the structure underlying the concept to be learned. Some knowledge of mathematics and theoretical computer science, including formal language theory, automata theory, formal grammars, and algorithmics, is a prerequisite for reading this book.

Related Products