Algebraic Geometry and Statistical Learning Theory - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Algebraic Geometry and Statistical Learning Theory write by Sumio Watanabe. This book was released on 2009-08-13. Algebraic Geometry and Statistical Learning Theory available in PDF, EPUB and Kindle. Sure to be influential, Watanabe's book lays the foundations for the use of algebraic geometry in statistical learning theory. Many models/machines are singular: mixture models, neural networks, HMMs, Bayesian networks, stochastic context-free grammars are major examples. The theory achieved here underpins accurate estimation techniques in the presence of singularities.
Computing in Algebraic Geometry
Computing in Algebraic Geometry - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Computing in Algebraic Geometry write by Wolfram Decker. This book was released on 2006-03-02. Computing in Algebraic Geometry available in PDF, EPUB and Kindle. This book provides a quick access to computational tools for algebraic geometry, the mathematical discipline which handles solution sets of polynomial equations. Originating from a number of intense one week schools taught by the authors, the text is designed so as to provide a step by step introduction which enables the reader to get started with his own computational experiments right away. The authors present the basic concepts and ideas in a compact way.
Computations in Algebraic Geometry with Macaulay 2
Computations in Algebraic Geometry with Macaulay 2 - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Computations in Algebraic Geometry with Macaulay 2 write by David Eisenbud. This book was released on 2013-03-14. Computations in Algebraic Geometry with Macaulay 2 available in PDF, EPUB and Kindle. This book presents algorithmic tools for algebraic geometry, with experimental applications. It also introduces Macaulay 2, a computer algebra system supporting research in algebraic geometry, commutative algebra, and their applications. The algorithmic tools presented here are designed to serve readers wishing to bring such tools to bear on their own problems. The first part of the book covers Macaulay 2 using concrete applications; the second emphasizes details of the mathematics.
Learning and Geometry: Computational Approaches
Learning and Geometry: Computational Approaches - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Learning and Geometry: Computational Approaches write by David Kueker. This book was released on 1995-12-01. Learning and Geometry: Computational Approaches available in PDF, EPUB and Kindle. The field of computational learning theory arose out of the desire to for mally understand the process of learning. As potential applications to artificial intelligence became apparent, the new field grew rapidly. The learning of geo metric objects became a natural area of study. The possibility of using learning techniques to compensate for unsolvability provided an attraction for individ uals with an immediate need to solve such difficult problems. Researchers at the Center for Night Vision were interested in solving the problem of interpreting data produced by a variety of sensors. Current vision techniques, which have a strong geometric component, can be used to extract features. However, these techniques fall short of useful recognition of the sensed objects. One potential solution is to incorporate learning techniques into the geometric manipulation of sensor data. As a first step toward realizing such a solution, the Systems Research Center at the University of Maryland, in conjunction with the Center for Night Vision, hosted a Workshop on Learning and Geometry in January of 1991. Scholars in both fields came together to learn about each others' field and to look for common ground, with the ultimate goal of providing a new model of learning from geometrical examples that would be useful in computer vision. The papers in the volume are a partial record of that meeting.
Algorithmic and Experimental Methods in Algebra, Geometry, and Number Theory
Algorithmic and Experimental Methods in Algebra, Geometry, and Number Theory - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Algorithmic and Experimental Methods in Algebra, Geometry, and Number Theory write by Gebhard Böckle. This book was released on 2018-03-22. Algorithmic and Experimental Methods in Algebra, Geometry, and Number Theory available in PDF, EPUB and Kindle. This book presents state-of-the-art research and survey articles that highlight work done within the Priority Program SPP 1489 “Algorithmic and Experimental Methods in Algebra, Geometry and Number Theory”, which was established and generously supported by the German Research Foundation (DFG) from 2010 to 2016. The goal of the program was to substantially advance algorithmic and experimental methods in the aforementioned disciplines, to combine the different methods where necessary, and to apply them to central questions in theory and practice. Of particular concern was the further development of freely available open source computer algebra systems and their interaction in order to create powerful new computational tools that transcend the boundaries of the individual disciplines involved. The book covers a broad range of topics addressing the design and theoretical foundations, implementation and the successful application of algebraic algorithms in order to solve mathematical research problems. It offers a valuable resource for all researchers, from graduate students through established experts, who are interested in the computational aspects of algebra, geometry, and/or number theory.
