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Simulation-Based Algorithms for Markov Decision Processes (Communications and Control Engineering)
Simulation-Based Algorithms for Markov Decision Processes (Communications and Control Engineering)
Markov decision process (MDP) models are widely used for modeling sequential decision-making problems that arise in engineering, economics, computer science, and the social sciences.  Many real-world problems modeled by MDPs have huge state and/or action spaces, giving an opening to the curse of dimensionality and so making practical...
Approximation Algorithms
Approximation Algorithms
Covering the basic techniques used in the latest research work, the author consolidates progress made so far, including some very recent and promising results, and conveys the beauty and excitement of work in the field. He gives clear, lucid explanations of key results and ideas, with intuitive proofs, and provides critical examples and numerous...
Theoretical Aspects of Computer Science: Advanced Lectures (Lecture Notes in Computer Science)
Theoretical Aspects of Computer Science: Advanced Lectures (Lecture Notes in Computer Science)
The First Summer School on Theoretical Aspects on Computer Science was held at the Institute for Studies in Theoretical Physics and Mathematics (IPM) from July 3-10, 2000.

The idea of organizing a summer school was originated during a conversation between the first and the second editor of this volume in the winter
...
Modern Algorithms for Image Processing: Computer Imagery by Example Using C#
Modern Algorithms for Image Processing: Computer Imagery by Example Using C#

Utilize modern methods for digital image processing and take advantage of the many time-saving templates provided for all of the projects in this book.

Modern Algorithms for Image Processing approaches the topic of image processing through teaching by example. Throughout the book, you will create projects...

Stochastic Approximation and Recursive Algorithms and Applications (Stochastic Modelling and Applied Probability) (v. 35)
Stochastic Approximation and Recursive Algorithms and Applications (Stochastic Modelling and Applied Probability) (v. 35)

This book presents a thorough development of the modern theory of stochastic approximation or recursive stochastic algorithms for both constrained and unconstrained problems. This second edition is a thorough revision, although the main features and structure remain unchanged. It contains many additional applications and results as...

The Mathematical Theory of Cosmic Strings (Series in High Energy Physics, Cosmology and Gravitation)
The Mathematical Theory of Cosmic Strings (Series in High Energy Physics, Cosmology and Gravitation)
Anderson provides a comprehensive summary and review of the mathematical theory of cosmic strings. The subject is not in a state of rapid change so the book is up to date and it is likely to remain so for some time. Although the book is technical and requires a strong mathematical background and an interest in differential geometry, it is well...
Bayesian Time Series Models
Bayesian Time Series Models

'What's going to happen next?' Time series data hold the answers, and Bayesian methods represent the cutting edge in learning what they have to say. This ambitious book is the first unified treatment of the emerging knowledge-base in Bayesian time series techniques. Exploiting the unifying framework of probabilistic graphical...

Introduction to Computation and Programming Using Python
Introduction to Computation and Programming Using Python

This book introduces students with little or no prior programming experience to the art of computational problem solving using Python and various Python libraries, including PyLab. It provides students with skills that will enable them to make productive use of computational techniques, including some of the tools and techniques of "data...

Data-Driven Modeling: Using MATLAB® in Water Resources and Environmental Engineering (Water Science and Technology Library)
Data-Driven Modeling: Using MATLAB® in Water Resources and Environmental Engineering (Water Science and Technology Library)

“Data-Driven Modeling: Using MATLAB® in Water Resources and Environmental Engineering” provides a systematic account of major concepts and methodologies for data-driven models and presents a unified framework that makes the subject more accessible to and applicable for researchers and practitioners. It integrates important...

Plastic Analysis and Design of Steel Structures
Plastic Analysis and Design of Steel Structures
Simple introduction to plastic analysis of complex steel structures

The plastic analysis method has been used extensively by engineers for designing steel structures. Simpler structures can be analyzed using the basic virtual work formulation, but more complex frames are evaluated with specialist computer software. This new
...
Meta-Learning in Computational Intelligence (Studies in Computational Intelligence)
Meta-Learning in Computational Intelligence (Studies in Computational Intelligence)

In the early days of pattern recognition and statistical data analysis life was rather simple: datasets were relatively small, collected from well-designed experiments, analyzed using a few methods that had good theoretical background. Explosive growth of the use of computers led to the creation of huge amounts of data of all kinds,...

Introduction to Finite Element Analysis Using MATLAB® and Abaqus
Introduction to Finite Element Analysis Using MATLAB® and Abaqus

There are some books that target the theory of the finite element, while others focus on the programming side of things. Introduction to Finite Element Analysis Using MATLAB® and Abaqus accomplishes both. This book teaches the first principles of the finite element method. It presents the theory of the finite...

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