Dual Models

An enthusiastic presentation of the complex set of uniform duals of uniform polyhedral shapes.

This is an excellent book on dual model and string theories. This updated issue of the author's book ?Dual Resonance Models? has new chapters on string theories added to it. This new volume therefore provides much background on the non-symmetrical aspects as well as modern development in the theory of strong interactions. This is a must for high energy physicists.

This is an excellent book on dual model and string theories. This updated issue of the author's book ‘Dual Resonance Models’ has new chapters on string theories added to it. This new volume therefore provides much background on the non-symmetrical aspects as well as modern development in the theory of strong interactions. This is a must for high energy physicists.

Many AI (and machine learning) tasks present in dual forms, e.g., English-to-Chinese translation vs. Chinese-to-English translation, speech recognition vs. speech synthesis,question answering vs. question generation, and image classification vs. image generation. Dual learning is a new learning framework that leverages the primal-dual structure of AI tasks to obtain effective feedback or regularization signals in order to enhance the learning/inference process. Since it was first introduced four years ago, the concept has attracted considerable attention in multiple fields, and been proven effective in numerous applications, such as machine translation, image-to-image translation, speech synthesis and recognition, (visual) question answering and generation, image captioning and generation, and code summarization and generation. Offering a systematic and comprehensive overview of dual learning, this book enables interested researchers (both established and newcomers) and practitioners to gain a better understanding of the state of the art in the field. It also provides suggestions for further reading and tools to help readers advance the area. The book is divided into five parts. The first part gives a brief introduction to machine learning and deep learning. The second part introduces the algorithms based on the dual reconstruction principle using machine translation, image translation, speech processing and other NLP/CV tasks as the demo applications. It covers algorithms, such as dual semi-supervised learning, dual unsupervised learning and multi-agent dual learning. In the context of image translation, it introduces algorithms including CycleGAN, DualGAN, DiscoGAN cdGAN and more recent techniques/applications. The third part presents various work based on the probability principle, including dual supervised learning and dual inference based on the joint-probability principle and dual semi-supervised learning based on the marginal-probability principle. The fourth part reviews various theoretical studies on dual learning and discusses its connections to other learning paradigms. The fifth part provides a summary and suggests future research directions.

Mean field approximation has been adopted to describe macroscopic phenomena from microscopic overviews. It is still in progress; fluid mechanics, gauge theory, plasma physics, quantum chemistry, mathematical oncology, non-equilibirum thermodynamics. spite of such a wide range of scientific areas that are concerned with the mean field theory, a unified study of its mathematical structure has not been discussed explicitly in the open literature. The benefit of this point of view on nonlinear problems should have significant impact on future research, as will be seen from the underlying features of self-assembly or bottom-up self-organization which is to be illustrated in a unified way. The aim of this book is to formulate the variational and hierarchical aspects of the equations that arise in the mean field theory from macroscopic profiles to microscopic principles, from dynamics to equilibrium, and from biological models to models that arise from chemistry and physics.

This informative volume presents the first comprehensive review of research and theory on dual-process models of social information processing. These models distinguish between qualitatively different modes of information processing in making decisions and solving problems (e.g., associative versus rule-based, controlled versus uncontrolled, and affective versus cognitive modes). Leading contributors review the basic assumptions of these approaches and review the ways they have been applied and tested in such areas as attitudes, stereotyping, person perception, memory, and judgment. Also examined are the relationships between different sets of processing modes, the factors that determine their utilization, and how they work in combination to affect responses to social information.

This book provides a postgraduate audience the keys they need to understand and further develop a set of tools for the efficient computation of lower bounds and valid inequalities in integer programs and combinatorial optimization problems. After discussing the classical approaches described in the literature, the book addresses how to extend these tools to other non-standard formulations that may be applied to a broad set of applications. Examples are provided to illustrate the underlying concepts and to pave the way for future contributions.

Combining narratological and stylistic methods, this book theorizes dual narrative dynamics consisting of plot development and covert progression and demonstrates the consequences for the interpretation of literary works. In narratives with such dynamics, writers work simultaneously with overt and covert trajectories of signification, establishing a range of relationships between them. The two parallel narrative movements may complement, contradict or even subvert each other, and these relationships significantly influence readers’ understanding not just of events but also of characters, themes, and aesthetic values. The book provides a systematic theoretical account of such previously neglected dual narrative dynamics, substantiated and enriched by the textual analysis of works by Ambrose Bierce, Kate Chopin, Franz Kafka, and Katherine Mansfield. The study explores the many ways that these authors have used dual dynamics to increase the power of their narratives. In addition, the book identifies the challenges such dual dynamics present not only for narratology but also for stylistics and translation studies, and it develops sound and provocative proposals for meeting those challenges. In taking an interdisciplinary approach, this book will appeal to scholars and students in the fields of narrative and literary theory, literary criticism, literary stylistics, and translation studies.