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  • Advanced Bayesian Signal Processing

    From Foundations to Frontiers in Communication and Sensing

    Series series Engineering (R0)
    This textbook provides a systematical introduction of Bayesian signal processing from Bayesian parameter estimation, factor graph, and message passing to sparse Bayesian inference (compressive sensing). The book not only provides a systematical introduction of the theory and methods in Bayesian inference, but also discusses advanced Bayesian inference methods recently developed for future wireless ... Read more

    $107.09 USD

  • Internet Video Data Streaming

    Energy-saving and Cost-aware Methods

    Series series Computer Science (R0)
    This book investigates the problem of reducing operating cost for a video streaming content delivery network (CDN), including both the CDN’s energy and traffic costs. It first introduces the key issues and design choices of representative real-world CDNs, and discusses the energy saving techniques for data centers and CDNs. Then, based on a measurement study on a large video streaming CDN, it ... Read more

    $49.49 USD

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    An Introduction

    Series series Adaptive Computation and Machine Learning series
    A detailed and up-to-date introduction to machine learning, presented through the unifying lens of probabilistic modeling and Bayesian decision theory.This book offers a detailed and up-to-date introduction to machine learning (including deep learning) through the unifying lens of probabilistic modeling and Bayesian decision theory. The book covers mathematical background (including linear algebra ... Read more

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  • Pattern Recognition

    This book considers classical and current theory and practice, of supervised, unsupervised and semi-supervised pattern recognition, to build a complete background for professionals and students of engineering. The authors, leading experts in the field of pattern recognition, have provided an up-to-date, self-contained volume encapsulating this wide spectrum of information. The very latest methods ... Read more

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  • Hands-On Mathematics for Deep Learning

    Build a solid mathematical foundation for training efficient deep neural networks

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    A comprehensive guide to getting well-versed with the mathematical techniques for building modern deep learning architecturesKey FeaturesUnderstand linear algebra, calculus, gradient algorithms, and other concepts essential for training deep neural networksLearn the mathematical concepts needed to understand how deep learning models functionUse deep learning for solving problems related to vision, ... Read more

    $27.89 USD or Free with Kobo Plus

  • Introduction to Data Compression

    by Khalid Sayood ...
    Series series The Morgan Kaufmann Series in Multimedia Information and Systems
    Introduction to Data Compression, Third Edition, is a concise and comprehensive guide to data compression. This book introduces the reader to the theory underlying today's compression techniques with detailed instruction for their applications using several examples to explain the concepts. Encompassing the entire field of data compression, it covers lossless and lossy compression, Huffman coding, ... Read more

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  • Practical Mathematics for AI and Deep Learning

    A Concise yet In-Depth Guide on Fundamentals of Computer Vision, NLP, Complex Deep Neural Networks and Machine Learning (English Edition)

    To construct a system that may be referred to as having ‘Artificial Intelligence,’ it is important to develop the capacity to design algorithms capable of performing data-based automated decision-making in conditions of uncertainty. Now, to accomplish this goal, one needs to have an in-depth understanding of the more sophisticated components of linear algebra, vector calculus, probability, and ... Read more

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  • Applied Geostatistics with SGeMS

    A User's Guide

    The Stanford Geostatistical Modeling Software (SGeMS) is an open-source computer package for solving problems involving spatially related variables. It provides geostatistics practitioners with a user-friendly interface, an interactive 3-D visualization, and a wide selection of algorithms. This practical book provides a step-by-step guide to using SGeMS algorithms. It explains the underlying ... Read more

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  • Machine Learning - A Journey To Deep Learning: With Exercises And Answers

    This unique compendium discusses some core ideas for the development and implementation of machine learning from three different perspectives — the statistical perspective, the artificial neural network perspective and the deep learning methodology.The useful reference text represents a solid foundation in machine learning and should prepare readers to apply and understand machine learning ... Read more

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  • Principles of Optimal Design

    Modeling and Computation

    Design optimization is a standard concept in engineering design, and in other disciplines which utilize mathematical decision-making methods. This textbook focuses on the close relationship between a design problem's mathematical model and the solution-driven methods which optimize it. Along with extensive material on modeling problems, this book also features useful techniques for checking ... Read more

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  • Introduction to Data Compression

    by Khalid Sayood ...
    Series series The Morgan Kaufmann Series in Multimedia Information and Systems
    Introduction to Data Compression, Fifth Edition, builds on the success of what is widely considered the best introduction and reference text on the art and science of data compression. Data compression techniques and technology are ever-evolving with new applications in image, speech, text, audio and video. This new edition includes all the latest developments in the field. Khalid Sayood provides ... Read more

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  • Graph Theoretic Methods in Multiagent Networks

    Series series Princeton Series in Applied Mathematics
    This accessible book provides an introduction to the analysis and design of dynamic multiagent networks. Such networks are of great interest in a wide range of areas in science and engineering, including: mobile sensor networks, distributed robotics such as formation flying and swarming, quantum networks, networked economics, biological synchronization, and social networks. Focusing on graph ... Read more

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