Graphical Models for Machine Learning and Digital Communication

Through a critical discussion of the issues surrounding the design, sharing and reuse of learning activities, the second edition of Rethinking Pedagogy for a Digital Age examines a wide range of persp

Reshape educational technology integration in classrooms to build truly transformative learning spaces. This concise, reader-friendly guide outlines a clear approach for properly and skillfully using

Digital medical imaging is one of the most important of clinical technologies; its use allows clinicians a noninvasive diagnostic tool and is advantageous for research. The objective of this book is t

This important book introduces the concept of intrusion detection, discusses various approaches for intrusion detection systems (IDS), and presents the architecture and implementation of IDS. It emph

"This book highlights important approaches to evaluating the creditability of digital sources and techniques used for various digital fields, presenting research in the area of computer mediated commu

The arrival of the participatory web 2.0 has been hailed by many as a media revolution, bringing with it new tools and possibilities for direct political action. Through specialised online platforms,

The arrival of the participatory web 2.0 has been hailed by many as a media revolution, bringing with it new tools and possibilities for direct political action. Through specialised online platforms,

This book focuses on the study of possible adaptive sampling mechanisms for haptic data compression aimed at applications like tele-operations and tele-surgery. Demonstrating that the selection of the

This book explores how multiculturalism should be promoted throughout higher education due to its benefits for students. It adopts a strengths-based student-centred perspective and offers practic

Machine learning is an interdisciplinary field of science and engineering that studies mathematical theories and practical applications of systems that learn. This book introduces theories, methods and applications of density ratio estimation, which is a newly emerging paradigm in the machine learning community. Various machine learning problems such as non-stationarity adaptation, outlier detection, dimensionality reduction, independent component analysis, clustering, classification and conditional density estimation can be systematically solved via the estimation of probability density ratios. The authors offer a comprehensive introduction of various density ratio estimators including methods via density estimation, moment matching, probabilistic classification, density fitting and density ratio fitting, as well as describing how these can be applied to machine learning. The book provides mathematical theories for density ratio estimation including parametric and non-parametric conve

Machine learning is an interdisciplinary field of science and engineering that studies mathematical theories and practical applications of systems that learn. This book introduces theories, methods and applications of density ratio estimation, which is a newly emerging paradigm in the machine learning community. Various machine learning problems such as non-stationarity adaptation, outlier detection, dimensionality reduction, independent component analysis, clustering, classification and conditional density estimation can be systematically solved via the estimation of probability density ratios. The authors offer a comprehensive introduction of various density ratio estimators including methods via density estimation, moment matching, probabilistic classification, density fitting and density ratio fitting, as well as describing how these can be applied to machine learning. The book provides mathematical theories for density ratio estimation including parametric and non-parametric conve

How much longer do you want to put it off? How long can you manage your organisation, your team or your life without making some fundamental change? Above all, how long can you avoid being overtaken b

This book examines and illustrates the potential of narrative technology, the integration and synthesis of storytelling and digital media in education. Storytelling is a foundational and powerful proc

In light of rapid advances in technology and changes in students’ learning styles,Leading Learning for Digital Natives offers much-needed new tools for guiding effective instruction in the classroom.

In light of rapid advances in technology and changes in students’ learning styles,Leading Learning for Digital Natives offers much-needed new tools for guiding effective instruction in the classroom.

Music Learning Today: Digital Pedagogy for Creating, Performing, and Responding to Music presents an approach to conceptualizing and utilizing technology as a tool for music learning. Designed for use

Music Learning Today: Digital Pedagogy for Creating, Performing, and Responding to Music presents an approach to conceptualizing and utilizing technology as a tool for music learning. Designed for use

Digital health data are the lifeblood of a continuous learning health system. A steady flow of reliable data is necessary to coordinate and monitor patient care, analyze and improve systems of care, c

This book provides practical strategies and examples for effectively integrating Web 2.0 tools into school library programs and the classroom curriculum. Aimed mainly at school librarians, this book e

Based on a major research project (the InterActive Project), this book explores and illustrates how digital technologies can transform learning across the curriculum. Using a wide range of educational

"This book develops an intelligent system to classify electrocardiogram signal classification signals for 4 common heart disorders, which are supraventricular tachycardia, bundle branch block, anterio

Designed to promote conversation about how to educate students for a rapidly changing, innovation-based world, this comprehensive and illuminating book from international education expert Vivien Stewa

Data assimilation is a hugely important mathematical technique, relevant in fields as diverse as geophysics, data science, and neuroscience. This modern book provides an authoritative treatment of the field as it relates to several scientific disciplines, with a particular emphasis on recent developments from machine learning and its role in the optimisation of data assimilation. Underlying theory from statistical physics, such as path integrals and Monte Carlo methods, are developed in the text as a basis for data assimilation, and the author then explores examples from current multidisciplinary research such as the modelling of shallow water systems, ocean dynamics, and neuronal dynamics in the avian brain. The theory of data assimilation and machine learning is introduced in an accessible and unified manner, and the book is suitable for undergraduate and graduate students from science and engineering without specialized experience of statistical physics.

This book constitutes revised selected papers from the 4th International Workshop on Graphical Models for Security, GraMSec 2017, held in Santa Barbara, CA, USA, in August 2017. The 5 full and 4 short