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  • Machine Learning Algorithms

    Adversarial Robustness in Signal Processing

    Series series Mathematics and Statistics (R0)
    This book demonstrates the optimal adversarial attacks against several important signal processing algorithms. Through presenting the optimal attacks in wireless sensor networks, array signal processing, principal component analysis, etc, the authors reveal the robustness of the signal processing algorithms against adversarial attacks. Since data quality is crucial in signal processing, the ... Read more

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    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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  • 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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  • Simulation-Based Algorithms for Markov Decision Processes

    Series series Engineering (R0)
    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 solution of the resulting models intractable. In other cases, the ... Read more

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  • Models, Algorithms, and Technologies for Network Analysis

    Proceedings of the Second International Conference on Network Analysis

    Series series Springer Nature Proceedings excluding Computer Science
    This volume contains two types of papers—a selection of contributions from the “Second International Conference in Network Analysis” held in Nizhny Novgorod on May 7–9, 2012, and papers submitted to an "open call for papers" reflecting the activities of LATNA at the Higher School for Economics.This volume contains many new results in modeling and powerful algorithmic solutions applied to problems ... Read more

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  • Computation, Cryptography, and Network Security

    Series series Mathematics and Statistics (R0)
    Analysis, assessment, and data management are core competencies for operation research analysts. This volume addresses a number of issues and developed methods for improving those skills. It is an outgrowth of a conference held in April 2013 at the Hellenic Military Academy, and brings together a broad variety of mathematical methods and theories with several applications. It discusses directions ... Read more

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  • Partially Observed Markov Decision Processes

    From Filtering to Controlled Sensing

    Covering formulation, algorithms, and structural results, and linking theory to real-world applications in controlled sensing (including social learning, adaptive radars and sequential detection), this book focuses on the conceptual foundations of partially observed Markov decision processes (POMDPs). It emphasizes structural results in stochastic dynamic programming, enabling graduate students ... Read more

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  • Hashing in Computer Science

    Fifty Years of Slicing and Dicing

    Written by one of the developers of the technology, Hashing is both a historical document on the development of hashing and an analysis of the applications of hashing in a society increasingly concerned with security. The material in this book is based on courses taught by the author, and key points are reinforced in sample problems and an accompanying instructor s manual. Graduate students and ... Read more

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  • Algorithms for Sparsity-Constrained Optimization

    Series series Engineering (R0)
    This thesis demonstrates techniques that provide faster and more accurate solutions to a variety of problems in machine learning and signal processing. The author proposes a "greedy" algorithm, deriving sparse solutions with guarantees of optimality. The use of this algorithm removes many of the inaccuracies that occurred with the use of previous models. ... Read more

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  • Numerical Analysis and Optimization

    NAO-III, Muscat, Oman, January 2014

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    Presenting the latest findings in the field of numerical analysis and optimization, this volume balances pure research with practical applications of the subject. Accompanied by detailed tables, figures, and examinations of useful software tools, this volume will equip the reader to perform detailed and layered analysis of complex datasets.Many real-world complex problems can be formulated as ... Read more

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  • Kalman Filtering

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    This new edition presents a thorough discussion of the mathematical theory and computational schemes of Kalman filtering. The filtering algorithms are derived via different approaches, including a direct method consisting of a series of elementary steps, and an indirect method based on innovation projection. Other topics include Kalman filtering for systems with correlated noise or colored noise, ... Read more

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    23rd International Conference, ASMTA 2016, Cardiff, UK, August 24-26, 2016, Proceedings

    Series series Springer Nature Proceedings Computer Science
    This book constitutes the refereed proceedings of the 23rd International Conference on Analytical and Stochastic Modelling Techniques and Applications, ASMTA 2016, held in Cardiff, UK, in August 2016.The 21 full papers presented in this book were carefully reviewed and selected from 30 submissions. The papers discuss the latest developments in analytical, numerical and simulation algorithms for ... Read more

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