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Anticipatory Optimization for Dynamic Decision Making (Operations Research/Computer Science Interfaces Series)
Anticipatory Optimization for Dynamic Decision Making (Operations Research/Computer Science Interfaces Series)

Anticipatory optimization for dynamic decision making relies on a number of different scientific disciplines. On a general level, the foundations of the field may be localized at the intersection of operations research, computer science and decision theory. Closer inspection reveals the important role of branches such as simulation,...

Word Processing in Groups
Word Processing in Groups

Connections between the theory of hyperbolic manifolds and the theory of automata are deeply interwoven in the history of mathematics of this century.

The use of symbol sequences to study dynamical systems originates in the work of Kocbe [Koc27, Koe29] and Morse [Mor87j, who both used symbol saliences to code geodesies on a...

Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques
Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques

This volume contains the papers presented at the 14th International Workshop on Approximation Algorithms for Combinatorial Optimization Problems (APPROX 2011) and the 15th International Workshop on Randomization and Computation (RANDOM 2011), which took place concurrently in Princeton University, USA, during August 17–19,...

Energy Minimization Methods in Computer Vision and Pattern Recognition: 8th International Conference, EMMCVPR 2011
Energy Minimization Methods in Computer Vision and Pattern Recognition: 8th International Conference, EMMCVPR 2011

Over the last few decades, energy minimization methods have become an established paradigm to resolve a variety of challenges in the fields of computer vision and pattern recognition. While traditional approaches to computer vision were often based on a heuristic sequence of processing steps and merely allowed a very limited...

Bioinformatics: The Machine Learning Approach, Second Edition (Adaptive Computation and Machine Learning)
Bioinformatics: The Machine Learning Approach, Second Edition (Adaptive Computation and Machine Learning)

We have been very pleased, beyond our expectations, with the reception of the first edition of this book. Bioinformatics, however, continues to evolve very rapidly, hence the need for a new edition. In the past three years, fullgenome sequencing has blossomed with the completion of the sequence of the fly and the first draft of the...

Text-to-Speech Synthesis
Text-to-Speech Synthesis

Text-to-Speech Synthesis provides a complete, end-to-end account of the process of generating speech by computer. Giving an in-depth explanation of all aspects of current speech synthesis technology, it assumes no specialized prior knowledge. Introductory chapters on linguistics, phonetics, signal processing and speech signals lay the...

The History of Approximation Theory: From Euler to Bernstein
The History of Approximation Theory: From Euler to Bernstein

The problem of approximating a given quantity is one of the oldest challenges faced by mathematicians. Its increasing importance in contemporary mathematics has created an entirely new area known as Approximation Theory. The modern theory was initially developed along two divergent schools of thought: the Eastern or Russian group, employing...

Bayesian Computation with R (Use R)
Bayesian Computation with R (Use R)
The book is a concise presentation of a wide range of Bayesian inferential problems and the computational methods to solve them. The detailed and thorough presentation style, with complete R code for the examples, makes it a welcome companion to a theoretical text on Bayesian inference.... Smart students of statistics will want to have both R and...
Advanced Signal Processing and Noise Reduction, 2nd Edition
Advanced Signal Processing and Noise Reduction, 2nd Edition

This book presents a broad range of theory and application of statistical signal processing. The emphasis is on digital noise reduction algorithms, particularly important in the field of mobile communication. Vaseghi covers a broad range of applications, including spectral estimation, channel equalization, speech coding over noisy channels,...

Probabilistic Methods for Algorithmic Discrete Mathematics (Algorithms and Combinatorics)
Probabilistic Methods for Algorithmic Discrete Mathematics (Algorithms and Combinatorics)
The book gives an accessible account of modern probabilistic methods for analyzing combinatorial structures and algorithms. It will be an useful guide for graduate students and researchers.
Special features included: a simple treatment of Talagrand's inequalities and their applications; an overview and many carefully worked out examples of the
...
Probability and Random Processes for Electrical and Computer Engineers
Probability and Random Processes for Electrical and Computer Engineers
The theory of probability is a powerful tool that helps electrical and computer engineers to explain, model, analyze, and design the technology they develop. The text begins at the advanced undergraduate level, assuming only a modest knowledge of probability, and progresses through more complex topics mastered at graduate level. The first five...
Advances In Quantitative Analysis Of Finance And Accounting
Advances In Quantitative Analysis Of Finance And Accounting
Advances in Quantitative Analysis of Finance and Accounting is an annual publication designed to disseminate developments in the quantitative analysis of finance and accounting. The publication is a forum for statistical and quantitative analyses of issues in finance and accounting, as well as applications of quantitative methods to problems in...
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