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Authority and Gender in Medieval and Renaissance Chronicles
This volume is an attempt to discuss the ways in which themes of authority and gender can be traced in the writing of chronicles and chronicle-like writings from the early Middle Ages to the Renaissance. With major contributions by fourteen authors, each of them specialists in the field, this study spans full across the compass of medieval and early modern Europe, from England and Scandinavia, to Byzantium and the Crusader Kingdoms; embraces a variety of media and methods; and touches evidence from diverse branches of learning such as language and literature, history and art, to name just a few. This is an important collection which will be of the highest utility for students and scholars of language, literature, and history for many years to come.
Graph Representation Learning
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 creating systems that can learn, reason, and generalize from this kind of data. Recent years have seen a surge in research on graph representation learning, including techniques for deep graph embeddings, generalizations of convolutional neural networks to graph-structured data, and neural message-passing approaches inspired by belief propagation. These advances in graph representation learning have led to new state-of-the-art results in numerous domains, including chemical sy...
Acute Ischemic Stroke
This updated second edition of Acute Ischemic Stroke: Imaging and Intervention provides a comprehensive account of the state of the art in the diagnosis and treatment of acute ischemic stroke. The basic format of the first edition has been retained, with sections on fundamentals such as pathophysiology and causes, imaging techniques and interventions. However, each chapter has been revised to reflect the important recent progress in advanced neuroimaging and the use of interventional tools. In addition, a new chapter is included on the classification instruments for ischemic stroke and their use in predicting outcomes and therapeutic triage. All of the authors are internationally recognized experts and members of the interdisciplinary stroke team at the Massachusetts General Hospital and Harvard Medical School. The text is supported by numerous informative illustrations, and ease of reference is ensured through the inclusion of suitable tables. This book will serve as a unique source of up-to-date information for neurologists, emergency physicians, radiologists and other health care providers who care for the patient with acute ischemic stroke.
Federated Learning
This book provides a comprehensive and self-contained introduction to federated learning, ranging from the basic knowledge and theories to various key applications. Privacy and incentive issues are the focus of this book. It is timely as federated learning is becoming popular after the release of the General Data Protection Regulation (GDPR). Since federated learning aims to enable a machine model to be collaboratively trained without each party exposing private data to others. This setting adheres to regulatory requirements of data privacy protection such as GDPR. This book contains three main parts. Firstly, it introduces different privacy-preserving methods for protecting a federated lear...
I Am the Tree of Life
"The Torah is called the Tree of Life. Just as a tree is always growing and changing, the Torah's ideas can help us grow and change, too. Yoga can do the same. Both can help us strengthen ourselves, calm our minds, and learn to appreciate the world around us. Written by rabbi and certified yoga instructor Mychal Copeland, I Am the Tree of Life encourages us to explore both the world of yoga and the stories of the Bible and find meaning in both"--Amazon.com.
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Representation Learning for Natural Language Processing
This open access book provides an overview of the recent advances in representation learning theory, algorithms and applications for natural language processing (NLP). It is divided into three parts. Part I presents the representation learning techniques for multiple language entries, including words, phrases, sentences and documents. Part II then introduces the representation techniques for those objects that are closely related to NLP, including entity-based world knowledge, sememe-based linguistic knowledge, networks, and cross-modal entries. Lastly, Part III provides open resource tools for representation learning techniques, and discusses the remaining challenges and future research directions. The theories and algorithms of representation learning presented can also benefit other related domains such as machine learning, social network analysis, semantic Web, information retrieval, data mining and computational biology. This book is intended for advanced undergraduate and graduate students, post-doctoral fellows, researchers, lecturers, and industrial engineers, as well as anyone interested in representation learning and natural language processing.
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Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications
This book constitutes the refereed post-conference proceedings of the 21st Iberoamerican Congress on Pattern Recognition, CIARP 2016, held in Lima, Peru, in November 2016. The 69 papers presented were carefully reviewed and selected from 131 submissions. The papers feature research results in the areas of pattern recognition, biometrics, image processing, computer vision, speech recognition, and remote sensing. They constitute theoretical as well as applied contributions in many fields related to the main topics of the conference.
