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  • Guide To Temporal Networks, A (Second Edition)

    Series Book 6 - Series On Complexity Science
    Network science offers a powerful language to represent and study complex systems composed of interacting elements — from the Internet to social and biological systems. A Guide to Temporal Networks presents recent theoretical and modelling progress in the emerging field of temporally varying networks and provides connections between the different areas of knowledge required to address this multi ... Read more

    $44.99 USD

  • Complex Networks and Their Applications VII

    Volume 1 Proceedings The 7th International Conference on Complex Networks and Their Applications COMPLEX NETWORKS 2018

    Series series Springer Nature Proceedings excluding Computer Science
    This book highlights cutting-edge research in the field of network science, offering scientists, researchers, students and practitioners a unique update on the latest advances in theory, together with a wealth of applications. It presents the peer-reviewed proceedings of the VII International Conference on Complex Networks and their Applications (COMPLEX NETWORKS 2018), which was held in Cambridge ... Read more

    $188.09 USD

  • Complex Networks and Their Applications VII

    Volume 2 Proceedings The 7th International Conference on Complex Networks and Their Applications COMPLEX NETWORKS 2018

    Series series Springer Nature Proceedings excluding Computer Science
    This book highlights cutting-edge research in the field of network science, offering scientists, researchers, students and practitioners a unique update on the latest advances in theory, together with a wealth of applications. It presents the peer-reviewed proceedings of the VII International Conference on Complex Networks and their Applications (COMPLEX NETWORKS 2018), which was held in Cambridge ... Read more

    $188.09 USD

  • Guide To Temporal Networks, A

    Series Book 4 - Series On Complexity Science
    Network science offers a powerful language to represent and study complex systems composed of interacting elements — from the Internet to social and biological systems. In its standard formulation, this framework relies on the assumption that the underlying topology is static, or changing very slowly as compared to dynamical processes taking place on it, e.g., epidemic spreading or navigation. ... Read more

    $35.09 USD

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    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

    $96.29 USD

  • Matrix Computations

    Series Book 3 - Johns Hopkins Studies in the Mathematical Sciences
    A comprehensive treatment of numerical linear algebra from the standpoint of both theory and practice.The fourth edition of Gene H. Golub and Charles F. Van Loan's classic is an essential reference for computational scientists and engineers in addition to researchers in the numerical linear algebra community. Anyone whose work requires the solution to a matrix problem and an appreciation of its ... Read more

    $63.99 USD

  • Machine Learning

    A Constraint-Based Approach

    by Marco Gori ...
    Machine Learning: A Constraint-Based Approach provides readers with a refreshing look at the basic models and algorithms of machine learning, with an emphasis on current topics of interest that includes neural networks and kernel machines. The book presents the information in a truly unified manner that is based on the notion of learning from environmental constraints. While regarding symbolic ... Read more

    $71.09 USD

  • Computational Number Theory and Modern Cryptography

    by Song Y. Yan ...
    The only book to provide a unified view of the interplay between computational number theory and cryptographyComputational number theory and modern cryptography are two of the most important and fundamental research fields in information security. In this book, Song Y. Yang combines knowledge of these two critical fields, providing a unified view of the relationships between computational number ... Read more

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  • Performance Analysis of Complex Networks and Systems

    This rigorous, self-contained book describes mathematical and, in particular, stochastic and graph theoretic methods to assess the performance of complex networks and systems. It comprises three parts: the first is a review of probability theory; Part II covers the classical theory of stochastic processes (Poisson, Markov and queueing theory), which are considered to be the basic building blocks ... Read more

    $91.09 USD

  • Kernel Methods and Machine Learning

    by S. Y. Kung ...
    Offering a fundamental basis in kernel-based learning theory, this book covers both statistical and algebraic principles. It provides over 30 major theorems for kernel-based supervised and unsupervised learning models. The first of the theorems establishes a condition, arguably necessary and sufficient, for the kernelization of learning models. In addition, several other theorems are devoted to ... Read more

    $98.39 USD

  • Neural-Based Orthogonal Data Fitting

    The EXIN Neural Networks

    Series Book 66 - Adaptive and Cognitive Dynamic Systems: Signal Processing, Learning, Communications and Control
    The presentation of a novel theory in orthogonal regressionThe literature about neural-based algorithms is often dedicated to principal component analysis (PCA) and considers minor component analysis (MCA) a mere consequence. Breaking the mold, Neural-Based Orthogonal Data Fitting is the first book to start with the MCA problem and arrive at important conclusions about the PCA problem.The book ... Read more

    $91.99 USD

  • Graph Representation Learning

    Series series Synthesis Lectures on Artificial Intelligence and Machine Learning
    This book is a foundational guide to graph representation learning, including state-of-the art advances, and introduces the highly successful graph neural network (GNN) formalism.Graph-structured data is ubiquitous throughout the natural and social sciences, from telecommunication networks to quantum chemistry. Building relational inductive biases into deep learning architectures is crucial for ... Read more

    $43.19 USD