Graphical Models for Machine Learning and Digital Communication

This book presents machine learning models and algorithms to address big data classification problems. Existing machine learning techniques like the decision tree (a hierarchical approach), random for

Linear Algebra and Linear Models comprises a concise and rigorous introduction to linear algebra required for statistics followed by the basic aspects of the theory of linear estimation and hypothesis

Graphical models in their modern form have been around since the late 1970s and appear today in many areas of the sciences. Along with the ongoing developments of graphical models, a number of differ

This Book discusses machine learning for model order reduction, which can be used in modern VLSI design to predict the behavior of an electronic circuit, via mathematical models that predict behavior.

This book brings together important topics of current research in probabilistic graphical modeling, learning from data and probabilistic inference. Coverage includes such topics as the characterizatio

This book discusses how to combine type-2 fuzzy sets and graphical models to solve a range of real-world pattern recognition problems such as speech recognition, handwritten Chinese character recognit

?This book is the result of a joint venture between Professor Akio Kawauchi, Osaka City University, well-known for his research in knot theory, and the Osaka study group of mathematics education, foun

This book develops a machine-learning framework for predicting economic growth. It can also be considered as a primer for using machine learning (also known as data mining or data analytics) to answer

This book addresses the theory and practice of using digital resources for contemporary learning, and how such resources can be designed, developed, and employed in a variety of learning activities an

The work presents new approaches to Machine Learning for Cyber Physical Systems, experiences and visions. It contains some selected papersfrom the international Conference ML4CPS – Machine Learn

Machine Learning Projects for .NET Developers shows you how to build smarter .NET applications that learn from data, using simple algorithms and techniques that can be applied to a wide range of real-

This book constitutes the refereed proceedings of the 7th International Workshop on Probabilistic Graphical Models, PGM 2014, held in Utrecht, The Netherlands, in September 2014. The 38 revised full p

Offering sequenced guidance for non-specialists on how to reap the benefits of machine learning in medicine and healthcare, this text harnesses the power of cutting-edge computing to maximize the acce

"Digital Communications" presents the theory and application of the philosophy of Digital Communication systems in a unique but lucid form. The book inserts equal importance to the theory and applicat

Underground mines require fool-proof, mine-wide communication systems for smooth functioning of mine production and worker safety. Proper and reliable communication systems not only decrease machine b

This book introduces the newly developed Extreme Learning Machine (ELM) including its theories and learning algorithms. ELM is a unified framework of broad type of generalized single-hidden layer feed

This authoritative and comprehensive title is designed to enhance best clinical practices for all healthcare providers who care for military service personnel and veterans. The book is organized into

You Must be Very Intelligent is the author’s account of studying for a PhD in a modern, successful university. Part-memoir and part-exposé, this book is highly entertaining and unusually revealing about the dubious morality and desperate behaviour which underpins competition in twenty-first century academia.This witty, warts-and-all account of Bodewits´ years as a PhD student in the august University of Edinburgh is full of success and failure, passion and pathos, insight, farce and warm-hearted disillusionment. She describes a world of collaboration and backstabbing; nefarious financing and wasted genius; cosmopolitan dreamers and discoveries that might just change the world… Is this a smart people’s world or a drip can of weird species? Modern academia is certainly darker and stranger than one might suspect…This book will put a wry, knowing smile on the faces of former researchers. And it is a cautionary parable for innocents who still believe that lofty academia is erected upon mora

The present book analyses critically the tripartite mimicry model (consisting of the mimic, model and receiver species) and develops semiotic tools for comparative analysis. It is proposed that mimicr

This book summarizes the current status of theoretical and experimental progress in 2 dimensional graphene-like monolayers and few-layers of transition metal dichalcogenides (TMDCs). Semiconducting monolayer TMDCs, due to the presence of a direct gap, significantly extend the potential of low-dimensional nanomaterials for applications in nanoelectronics and nano-optoelectronics as well as flexible nano-electronics with unprecedented possibilities to control the gap by external stimuli. Strong quantum confinement results in extremely high exciton binding energies which forms an interesting platform for both fundamental studies and device applications. Breaking of spatial inversion symmetry in monolayers results in strong spin-valley coupling potentially leading to their use in valleytronics.Starting with the basic chemistry of transition metals, the reader is introduced to the rich field of transition metal dichalcogenides. After a chapter on three dimensional crystals and a descri

Pro Spring Boot is your authoritative hands-on practical guide for increasing your Spring Framework-based enterprise Java and cloud application productivity while decreasing development time using the

The goal of these notes is to provide a fast introduction to symplectic geometry for graduate students with some knowledge of differential geometry, de Rham theory and classical Lie groups.This text a

The book covers tools in the study of online social networks such as machine learning techniques, clustering, and deep learning. A variety of theoretical aspects, application domains, and case studies

The aim of this volume entitled Digital Technologies: Sustainable Innovations for improving Teaching and Learning is to contribute in the global discussion on digital technologies as the means to fost

This is the first textbook on a generally applicable control strategy for turbulence and other complex nonlinear systems. The approach of the book employs powerful methods of machine learning for opti

This book offers a framework for the analysis of political communication in election campaigns based on digital trace data that documents political behavior, interests and opinions. The author investi

The current book is the first publication of a complete overview of machine learning methodologies for the medical and health sector. It was written as a training companion and as a must-read, not onl

This book provides a wide variety of algorithms and models to integrate linguistic knowledge into Statistical Machine Translation (SMT). It helps advance conventional SMT to linguistically motivated S

Digital games offer enormous potential for learning and engagement in mathematics ideas and processes. This volume offers multidisciplinary perspectives—of educators, cognitive scientists, psychologis

Machine learning is concerned with the analysis of large data and multiple variables. However, it is also often more sensitive than traditional statistical methods to analyze small data. The first vol

Machine learning is a novel discipline concerned with the analysis of large and multiple variables data. It involves computationally intensive methods, like factor analysis, cluster analysis, and disc

?This Springer Briefs volume guides the reader in a comprehensive form to design new digital business models. The book provides strategic roadmaps for enterprises in the digital world, and a comprehen

This introduction can be used, at the beginning graduate level, for a one-semester course on probability theory or for self-direction without benefit of a formal course; the measure theory needed is d

This book constitutes the post-conference proceedings of the 4th International Conference on Machine Learning, Optimization, and Data Science, LOD 2018, held in Volterra, Italy, in September 2018.The

This book aims to provide insight into how digital technologies may bridge and enhance formal and informal workplace learning. It features four major themes:1. Current research exploring the theoretic

This book is intended for use in advanced graduate courses in statistics / machine learning, as well as for all experimental neuroscientists seeking to understand statistical methods at a deeper level

This book is a synthesis of the complex interdependencies between user interface design of digital screen and learning process. It is analyzed the impact of digital revolution on learning, phases of d

This book covers the key ideas that link probability, statistics, and machine learning illustrated using Python modules in these areas. The entire text, including all the figures and n

This book presents basic ideas of machine learning in a way that is easy to understand, by providing hands-on practical advice, using simple examples, and motivating students with discussions of inter

?This book provides a complete overview of the role of machine learning in radiation oncology and medical physics, covering basic theory, methods, and a variety of applications in medical physics and