Learn IT - Books tags bayesian

Modeling with Data: Tools and Techniques for Scientific Computing

Princeton Press, 2008

I am a psychiatric geneticist but my degree is in neuroscience, which means that I now do far more statistics than I have been trained for. I cannot overstate to you the magnitude of the change in my productivity since finding this book. Even after reading the first few chapters, which explain why data analysis is painful and how one can implement...

Research and Development in Intelligent Systems XXVII

Springer, 2010

The papers in this volume are the refereed papers presented at AI-2010, the Thirtieth SGAI International Conference on Innovative Techniques and Applications of Artificial Intelligence, held in Cambridge in December 2010 in both the technical and the application streams. They present new and innovative developments and applications, divided...

Foundations Of Decision-Making Agents: Logic, Probability and Modality

World Scientific Publishing, 2008

This self-contained book provides three fundamental and generic approaches (logical, probabilistic, and modal) to representing and reasoning with agent epistemic states, specifically in the context of decision making. Each of these approaches can be applied to the construction of intelligent software agents for making decisions, thereby...

Numerical Methods for Chemical Engineering: Applications in MATLAB

Cambridge University Press, 2006

Suitable for a first year graduate course, this textbook unites the applications of numerical mathematics and scientific computing to the practice of chemical engineering. Written in a pedagogic style, the book describes basic linear and nonlinear algebric systems all the way through to stochastic methods, Bayesian statistics and parameter...

Multimedia Signal Processing: Theory and Applications in Speech, Music and Communications

John Wiley & Sons, 2007

Multimedia Signal Processing is a comprehensive and accessible text to the theory and applications of digital signal processing (DSP). The applications of DSP are pervasive and include multimedia systems, cellular communication, adaptive network management, radar, pattern recognition, medical signal processing, financial data...

Applied Data Mining: Statistical Methods for Business and Industry

John Wiley & Sons, 2003

"…a book with many nice features that has elements of interest for …every subset of the intended audience…"
(Journal of the American Statistical Association, September 2006)

"The author's style is consistently readable. Stripping out all but the barest essential...

Data Mining: Opportunities and Challenges

Idea Group Publishing, 2003

An overview of the multidisciplinary field of data mining, this book focuses specifically on new methodologies and case studies. Included are case studies written by 44 leading scientists and talented young scholars from seven different countries. Topics covered include data mining based on rough sets, the impact of missing data, and mining free...

Advanced Digital Signal Processing and Noise Reduction

John Wiley & Sons, 2009

Digital signal processing plays a central role in the development of modern communication and information processing systems. The theory and application of signal processing is concerned with the identification, modelling and utilisation of patterns and structures in a signal process. The observation signals are often distorted, incomplete...

Online Damage Detection in Structural Systems: Applications of Proper Orthogonal Decomposition, and Kalman and Particle Filters (SpringerBriefs in Applied Sciences and Technology)

Springer, 2014

This monograph assesses in depth the application of recursive Bayesian filters in structural health monitoring. Although the methods and algorithms used here are well established in the field of automatic control, their application in the realm of civil engineering has to date been limited. The monograph is therefore intended as a reference...

Mathematical Statistics with Applications

Academic Press, 2009

This textbook is of an interdisciplinary nature and is designed for a two- or one-semester course in probability and statistics, with basic calculus as a prerequisite. The book is primarily written to give a sound theoretical introduction to statistics while emphasizing applications. If teaching statistics is the main purpose of a...

Advances in Intelligent Signal Processing and Data Mining: Theory and Applications (Studies in Computational Intelligence)

Springer, 2012

The book presents some of the most efficient statistical and deterministic methods for information processing and applications in order to extract targeted information and find hidden patterns. The techniques presented range from Bayesian approaches and their variations such as sequential Monte Carlo methods, Markov Chain Monte Carlo filters,...

Gaussian Processes for Machine Learning (Adaptive Computation and Machine Learning)

MIT Press, 2005

Gaussian processes (GPs) provide a principled, practical, probabilistic approach to learning in kernel machines. GPs have received increased attention in the machine-learning community over the past decade, and this book provides a long-needed systematic and unified treatment of theoretical and practical aspects of GPs in machine learning. The...

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