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Computer Science and Intelligent Systems

Computer Science and Intelligent Systems

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Sparse modeling is a rapidly developing area at the intersection of statistical learning and signal processing, motivated by the age-old statistical problem of selecting a small number of predictive variables in high-dimensional datasets. This collection describes key approaches in sparse modeling, focusing on its applications in fields including neuroscience, computational biology, and computer vision.

Category theory was invented in the 1940s to unify and synthesize different areas in mathematics, and it has proven remarkably successful in enabling powerful communication between disparate fields and subfields within mathematics. This book shows that category theory can be useful outside of mathematics as a rigorous, flexible, and coherent modeling language throughout the sciences.

Complex communicating computer systems—computers connected by data networks and in constant communication with their environments—do not always behave as expected. This book introduces behavioral modeling, a rigorous approach to behavioral specification and verification of concurrent and distributed systems. It is among the very few techniques capable of modeling systems interaction at a level of abstraction sufficient for the interaction to be understood and analyzed.

Basics and Extensions

Spreadsheets are used daily by millions of people for tasks that range from organizing a list of addresses to carrying out complex economic simulations. Spreadsheet programs are easy to learn and convenient to use because they have a clear visual model and a simple efficient underlying computational model. Yet although the basic spreadsheet model could be extended, improved, or otherwise experimented with in many ways, there is no coherently designed, reasonably efficient open source spreadsheet implementation that is a suitable platform for such experiments.

The goal of machine learning is to program computers to use example data or past experience to solve a given problem. Many successful applications of machine learning exist already, including systems that analyze past sales data to predict customer behavior, optimize robot behavior so that a task can be completed using minimum resources, and extract knowledge from bioinformatics data. Introduction to Machine Learning is a comprehensive textbook on the subject, covering a broad array of topics not usually included in introductory machine learning texts.

All design is situated—carried out from an embedded position. Design involves many participants and encompasses a range of interactions and interdependencies among designers, designs, design methods, and users. Design is also multidisciplinary, extending beyond the traditional design professions into such domains as health, culture, education, and transportation. This book presents eighteen situated design methods, offering cases and analyses of projects that range from designing interactive installations, urban spaces, and environmental systems to understanding customer experiences.

The Algorithmics of Ancestral Recombination Graphs and Explicit Phylogenetic Networks

In this book, Dan Gusfield examines combinatorial algorithms to construct genealogical and exact phylogenetic networks, particularly ancestral recombination graphs (ARGs). The algorithms produce networks (or information about networks) that serve as hypotheses about the true genealogical history of observed biological sequences and can be applied to practical biological problems.

Proceedings of the Fourteenth International Conference on the Synthesis and Simulation of Living Systems

ALIFE 14, the Fourteenth International Conference on the Synthesis and Simulation of Living Systems, presents the current state of the art of Artificial Life—the highly interdisciplinary research area on artificially constructed living systems, including mathematical, computational, robotic, and biochemical ones. The understanding and application of such generalized forms of life, or “life as it could be,” have been producing significant contributions to various fields of science and engineering.

Designs for Living Online

Computers were first conceived as “thinking machines,” but in the twenty-first century they have become social machines, online places where people meet friends, play games, and collaborate on projects. In this book, Judith Donath argues persuasively that for social media to become truly sociable media, we must design interfaces that reflect how we understand and respond to the social world.

Mixing Human-Computer Interactions with Human-Food Interactions

Our contemporary concerns about food range from food security to agricultural sustainability to getting dinner on the table for family and friends. This book investigates food issues as they intersect with participatory Internet culture—blogs, wikis, online photo- and video-sharing platforms, and social networks—in efforts to bring about a healthy, socially inclusive, and sustainable food future.

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