Proceedings of the Workshop on Neural Network Applications and Tools, September 13-14, 1993, Liverpool, England PDF Download
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Author: Paulo J. G. Lisboa
Publisher:
ISBN:
Category : Computers
Languages : en
Pages : 166
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Book Description
Author:
Publisher:
ISBN:
Category : Neural circuitry
Languages : en
Pages : 840
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Book Description
Author: Roland Koebarle
Publisher: World Scientific
ISBN: 9813201215
Category : Science
Languages : en
Pages : 335
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Book Description
Emphasis of the proceedings is on the performance of neural networks through selection of the complex state structure of spin glasses in condensed matter physics.
Author: Eric D. Kolaczyk
Publisher: Springer Science & Business Media
ISBN: 0387881468
Category : Computers
Languages : en
Pages : 397
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Book Description
In recent years there has been an explosion of network data – that is, measu- ments that are either of or from a system conceptualized as a network – from se- ingly all corners of science. The combination of an increasingly pervasive interest in scienti c analysis at a systems level and the ever-growing capabilities for hi- throughput data collection in various elds has fueled this trend. Researchers from biology and bioinformatics to physics, from computer science to the information sciences, and from economics to sociology are more and more engaged in the c- lection and statistical analysis of data from a network-centric perspective. Accordingly, the contributions to statistical methods and modeling in this area have come from a similarly broad spectrum of areas, often independently of each other. Many books already have been written addressing network data and network problems in speci c individual disciplines. However, there is at present no single book that provides a modern treatment of a core body of knowledge for statistical analysis of network data that cuts across the various disciplines and is organized rather according to a statistical taxonomy of tasks and techniques. This book seeks to ll that gap and, as such, it aims to contribute to a growing trend in recent years to facilitate the exchange of knowledge across the pre-existing boundaries between those disciplines that play a role in what is coming to be called ‘network science.
Author: Paulo J. G. Lisboa
Publisher:
ISBN:
Category : Computers
Languages : en
Pages : 166
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Book Description
Author: Taylor Arnold
Publisher: CRC Press
ISBN: 1351694758
Category : Business & Economics
Languages : en
Pages : 352
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Book Description
A Computational Approach to Statistical Learning gives a novel introduction to predictive modeling by focusing on the algorithmic and numeric motivations behind popular statistical methods. The text contains annotated code to over 80 original reference functions. These functions provide minimal working implementations of common statistical learning algorithms. Every chapter concludes with a fully worked out application that illustrates predictive modeling tasks using a real-world dataset. The text begins with a detailed analysis of linear models and ordinary least squares. Subsequent chapters explore extensions such as ridge regression, generalized linear models, and additive models. The second half focuses on the use of general-purpose algorithms for convex optimization and their application to tasks in statistical learning. Models covered include the elastic net, dense neural networks, convolutional neural networks (CNNs), and spectral clustering. A unifying theme throughout the text is the use of optimization theory in the description of predictive models, with a particular focus on the singular value decomposition (SVD). Through this theme, the computational approach motivates and clarifies the relationships between various predictive models. Taylor Arnold is an assistant professor of statistics at the University of Richmond. His work at the intersection of computer vision, natural language processing, and digital humanities has been supported by multiple grants from the National Endowment for the Humanities (NEH) and the American Council of Learned Societies (ACLS). His first book, Humanities Data in R, was published in 2015. Michael Kane is an assistant professor of biostatistics at Yale University. He is the recipient of grants from the National Institutes of Health (NIH), DARPA, and the Bill and Melinda Gates Foundation. His R package bigmemory won the Chamber's prize for statistical software in 2010. Bryan Lewis is an applied mathematician and author of many popular R packages, including irlba, doRedis, and threejs.
Author: USENIX Association
Publisher: Usenix Association
ISBN:
Category : Computers
Languages : en
Pages : 156
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Author:
Publisher:
ISBN:
Category : Weights and measures
Languages : en
Pages : 52
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Author:
Publisher:
ISBN:
Category : Automatic data collection systems
Languages : en
Pages : 0
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Book Description
Author: Wang, Yun
Publisher: IGI Global
ISBN: 1599047101
Category : Computers
Languages : en
Pages : 476
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Book Description
Provides statistical modeling and simulating approaches to address the needs for intrusion detection and protection. Covers topics such as network traffic data, anomaly intrusion detection, and prediction events.
Author: Charu C. Aggarwal
Publisher: Springer Science & Business Media
ISBN: 0387475346
Category : Computers
Languages : en
Pages : 365
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Book Description
This book primarily discusses issues related to the mining aspects of data streams and it is unique in its primary focus on the subject. This volume covers mining aspects of data streams comprehensively: each contributed chapter contains a survey on the topic, the key ideas in the field for that particular topic, and future research directions. The book is intended for a professional audience composed of researchers and practitioners in industry. This book is also appropriate for advanced-level students in computer science.
