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Say What You Will
“A unique and unforgettable love.” —Teen Vogue John Green's The Fault in Our Stars meets Rainbow Rowell's Eleanor & Park in this beautifully written, incredibly honest, and emotionally poignant novel. Cammie McGovern's insightful young adult debut is a heartfelt and heartbreaking story about how we can all feel lost until we find someone who loves us because of our faults, not in spite of them. Born with cerebral palsy, Amy can't walk without a walker, talk without a voice box, or even fully control her facial expressions. Plagued by obsessive-compulsive disorder, Matthew is consumed with repeated thoughts, neurotic rituals, and crippling fear. Both in desperate need of someone to help them reach out to the world, Amy and Matthew are more alike than either ever realized. When Amy decides to hire student aides to help her in her senior year at Coral Hills High School, these two teens are thrust into each other's lives. As they begin to spend time with each other, what started as a blossoming friendship eventually grows into something neither expected.
Abstraction, Reformulation, and Approximation
It has been recognized since the inception of Artificial Intelligence (AI) that abstractions, problem reformulations, and approximations (AR&A) are central to human common sense reasoning and problem solving and to the ability of systems to reason effectively in complex domains. AR&A techniques have been used to solve a variety of tasks, including automatic programming, constraint satisfaction, design, diagnosis, machine learning, search, planning, reasoning, game playing, scheduling, and theorem proving. The primary purpose of AR&A techniques in such settings is to overcome computational intractability. In addition, AR&A techniques are useful for accelerating learning and for summarizing se...
Machine Learning and Data Mining Approaches to Climate Science
This book presents innovative work in Climate Informatics, a new field that reflects the application of data mining methods to climate science, and shows where this new and fast growing field is headed. Given its interdisciplinary nature, Climate Informatics offers insights, tools and methods that are increasingly needed in order to understand the climate system, an aspect which in turn has become crucial because of the threat of climate change. There has been a veritable explosion in the amount of data produced by satellites, environmental sensors and climate models that monitor, measure and forecast the earth system. In order to meaningfully pursue knowledge discovery on the basis of such voluminous and diverse datasets, it is necessary to apply machine learning methods, and Climate Informatics lies at the intersection of machine learning and climate science. This book grew out of the fourth workshop on Climate Informatics held in Boulder, Colorado in Sep. 2014.
Coasts in Crisis
Human settlement of the coastal zone -- Coastal tectonics and hazards -- Tropical cyclones, hurricanes and typhoons -- Storms, waves, coastal erosion and shoreline retreat -- Climate change and sea-level rise
Machine Learning: ECML 2002
This book constitutes the refereed preceedings of the 13th European Conference on Machine Learning, ECML 2002, held in Helsinki, Finland in August 2002. The 41 revised full papers presented together with 4 invited contributions were carefully reviewed and selected from numerous submissions. Among the topics covered are computational discovery, search strategies, Classification, support vector machines, kernel methods, rule induction, linear learning, decision tree learning, boosting, collaborative learning, statistical learning, clustering, instance-based learning, reinforcement learning, multiagent learning, multirelational learning, Markov decision processes, active learning, etc.
Graph Mining
What does the Web look like? How can we find patterns, communities, outliers, in a social network? Which are the most central nodes in a network? These are the questions that motivate this work. Networks and graphs appear in many diverse settings, for example in social networks, computer-communication networks (intrusion detection, traffic management), protein-protein interaction networks in biology, document-text bipartite graphs in text retrieval, person-account graphs in financial fraud detection, and others. In this work, first we list several surprising patterns that real graphs tend to follow. Then we give a detailed list of generators that try to mirror these patterns. Generators are ...
Design(s) for Law
Legal design has been with us for over a decade. Its core idea, i.e. to use design methods to make the world of law accessible to all, has been widely embraced by academics, researchers, and professionals. Over time, the field has grown, expanding its initial problem-solving approach to other dimensions of design, such as speculative design, design fiction, proactive law, and disciplines like cognitive science and philosophy. The book presents a state-of-the-art reflection on legal design evolution and applications. It features twelve insightful contributions discussed during the 2023 'Legal Design Roundtable' on 'Design(s) for Law', organised within the Erasmus+ Jean Monnet clinic on 'EU Digital Rights, Law, and Design'. These perspectives from academics and professionals add important nuances to the literature, either presenting new approaches, applying consolidated practices to new contexts and areas, or showcasing actual and potential applications. Ideal for academics, legal professionals, and students, this book is a must-read for anyone interested in new critical approaches to the law and in the creative construction of fairer and more human-friendly legal systems.
Artificial Intelligence in Forecasting
Forecasting deals with the uncertainty of the future. To be effective, forecasting models should be timely available, accurate, reliable, and compatible with existing database. Accurate projection of the future is of vital importance in supply chain management, inventory control, economic condition, technology, growth trend, social change, political change, business, weather forecasting, stock price prediction, earthquake prediction, etc. AI powered tools and techniques of forecasting play a major role in improving the projection accuracy. The software running AI forecasting models use machine learning to improve accuracy. The software can analyse the past data and can make better prediction about the future trends with higher accuracy and confidence that favours for making proper future planning and decision. In other words, accurate forecasting requires more than just the matching of models to historical data. The book covers the latest techniques used by managers in business today, discover the importance of forecasting and learn how it's accomplished. Readers will also be familiarised with the necessary skills to meet the increased demand for thoughtful and realistic forecasts.
Data Mining for Geoinformatics
The rate at which geospatial data is being generated exceeds our computational capabilities to extract patterns for the understanding of a dynamically changing world. Geoinformatics and data mining focuses on the development and implementation of computational algorithms to solve these problems. This unique volume contains a collection of chapters on state-of-the-art data mining techniques applied to geoinformatic problems of high complexity and important societal value. Data Mining for Geoinformatics addresses current concerns and developments relating to spatio-temporal data mining issues in remotely-sensed data, problems in meteorological data such as tornado formation, estimation of radi...
