Conditionals and Prediction


Book Description

This book offers a new and in-depth analysis of English conditional sentences. In a wide-ranging discussion, Dancygier classifies conditional constructions according to time-reference and modality. She shows how the basic meaning parameters of conditionality correlate to formal parameters of the linguistic constructions which are used to express them. Dancygier suggests that the function of prediction is central to the definition of conditionality, and that conditional sentences display certain formal features which correlate to aspects of interpretation. Although the analysis is based primarily on English, it provides a theoretical framework that can be extended cross-linguistically to a broad range of grammatical phenomena. It will be essential reading for scholars and students concerned with the role of conditionals in English and many other languages.




Mental Spaces in Grammar


Book Description

Conditional constructions have long fascinated linguists, grammarians and philosophers. In this pioneering new study, Barbara Dancygier and Eve Sweetser offer a new descriptive framework for the study of conditionality, broadening the range of richly described conditional constructions. They explore theoretical issues such as the mental-space-building processes underlying conditional thinking and the form-meaning relationship involved in expressing conditionality. Using a broad range of attested English conditional constructions, the book examines inter-constructional relationships. Within the framework of Mental Spaces Theory, shared parameters of meaning are shown to be relevant to conditional constructions generally, as well as related temporal and causal constructions. This significant contribution to the field will be welcomed by a wide range of researchers in theoretical and cognitive linguistics.




Prediction


Book Description

Based upon ten case studies, Prediction explores how science-based predictions guide policy making and what this means in terms of global warming, biogenetically modifying organisms and polluting the environment with chemicals.




Identification for Prediction and Decision


Book Description

This book is a full-scale exposition of Charles Manski's new methodology for analyzing empirical questions in the social sciences. He recommends that researchers first ask what can be learned from data alone, and then ask what can be learned when data are combined with credible weak assumptions. Inferences predicated on weak assumptions, he argues, can achieve wide consensus, while ones that require strong assumptions almost inevitably are subject to sharp disagreements. Building on the foundation laid in the author's Identification Problems in the Social Sciences (Harvard, 1995), the book's fifteen chapters are organized in three parts. Part I studies prediction with missing or otherwise incomplete data. Part II concerns the analysis of treatment response, which aims to predict outcomes when alternative treatment rules are applied to a population. Part III studies prediction of choice behavior. Each chapter juxtaposes developments of methodology with empirical or numerical illustrations. The book employs a simple notation and mathematical apparatus, using only basic elements of probability theory.




Prediction, Learning, and Games


Book Description

This important text and reference for researchers and students in machine learning, game theory, statistics and information theory offers a comprehensive treatment of the problem of predicting individual sequences. Unlike standard statistical approaches to forecasting, prediction of individual sequences does not impose any probabilistic assumption on the data-generating mechanism. Yet, prediction algorithms can be constructed that work well for all possible sequences, in the sense that their performance is always nearly as good as the best forecasting strategy in a given reference class. The central theme is the model of prediction using expert advice, a general framework within which many related problems can be cast and discussed. Repeated game playing, adaptive data compression, sequential investment in the stock market, sequential pattern analysis, and several other problems are viewed as instances of the experts' framework and analyzed from a common nonstochastic standpoint that often reveals new and intriguing connections.




Interpretable Machine Learning


Book Description

This book is about making machine learning models and their decisions interpretable. After exploring the concepts of interpretability, you will learn about simple, interpretable models such as decision trees, decision rules and linear regression. Later chapters focus on general model-agnostic methods for interpreting black box models like feature importance and accumulated local effects and explaining individual predictions with Shapley values and LIME. All interpretation methods are explained in depth and discussed critically. How do they work under the hood? What are their strengths and weaknesses? How can their outputs be interpreted? This book will enable you to select and correctly apply the interpretation method that is most suitable for your machine learning project.




Advances in Parallel, Distributed Computing


Book Description

This book constitutes the refereed proceedings of the First International Conference on Advances in Parallel, Distributed Computing Technologies and Applications, PDCTA 2011, held in Tirunelveli, India, in September 2011. The 64 revised full papers were carefully reviewed and selected from over 400 submissions. Providing an excellent international forum for sharing knowledge and results in theory, methodology and applications of parallel, distributed computing the papers address all current issues in this field with special focus on algorithms and applications, computer networks, cyber trust and security, wireless networks, as well as mobile computing and bioinformatics.




Life-Cycle of Engineering Systems: Emphasis on Sustainable Civil Infrastructure


Book Description

This volume contains the papers presented at IALCCE2016, the fifth International Symposium on Life-Cycle Civil Engineering (IALCCE2016), to be held in Delft, The Netherlands, October 16-19, 2016. It consists of a book of extended abstracts and a DVD with full papers including the Fazlur R. Khan lecture, keynote lectures, and technical papers from all over the world. All major aspects of life-cycle engineering are addressed, with special focus on structural damage processes, life-cycle design, inspection, monitoring, assessment, maintenance and rehabilitation, life-cycle cost of structures and infrastructures, life-cycle performance of special structures, and life-cycle oriented computational tools. The aim of the editors is to provide a valuable source for anyone interested in life-cycle of civil infrastructure systems, including students, researchers and practitioners from all areas of engineering and industry.




Intelligent Computing Methodologies


Book Description

This three-volume set LNCS 10361, LNCS 10362, and LNAI 10363 constitutes the refereed proceedings of the 13th International Conference on Intelligent Computing, ICIC 2017, held in Liverpool, UK, in August 2017. The 212 full papers and 20 short papers of the three proceedings volumes were carefully reviewed and selected from 612 submissions. This third volume of the set comprises 67 papers. The papers are organized in topical sections such as Intelligent Computing in Robotics; Intelligent Computing in Computer Vision; Intelligent Control and Automation; Intelligent Agent and Web Applications; Fuzzy Theory and Algorithms; Supervised Learning; Unsupervised Learning; Kernel Methods and Supporting Vector Machines; Knowledge Discovery and Data Mining; Natural Language Processing and Computational Linguistics; Advances of Soft Computing: Algorithms and Its Applications - Rozaida Ghazali; Advances in Swarm Intelligence Algorithm; Computational Intelligence and Security for Image Applications in SocialNetwork; Biomedical Image Analysis; Information Security; Machine Learning; Intelligent Data Analysis and Prediction.




Innovative Computing Methods and their Applications to Engineering Problems


Book Description

The design of most modern engineering systems entails the consideration of a good trade-off between the several targets requirements to be satisfied along the system life such as high reliability, low redundancy and low operational costs. These aspects are often in conflict with one another, hence a compromise solution has to be sought. Innovative computing techniques, such as genetic algorithms, swarm intelligence, differential evolution, multi-objective evolutionary optimization, just to name few, are of great help in founding effective and reliable solution for many engineering problems. Each chapter of this book attempts to using an innovative computing technique to elegantly solve a different engineering problem.