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  • Artificial intelligence  (8)
  • 550 - Earth sciences
  • Chemical Engineering
  • Chemistry
  • Life and Medical Sciences
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  • The MIT Press  (9)
  • English  (9)
  • 2020-2024  (9)
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  • English  (9)
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  • 2020-2024  (9)
  • 2000-2004
  • 1970-1974
  • 1965-1969
  • 1955-1959
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  • 1
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    Boosting (2022)
    The MIT Press | The MIT Press
    Details
    Publication Date: 2024-04-14
    Description: An accessible introduction and essential reference for an approach to machine learning that creates highly accurate prediction rules by combining many weak and inaccurate ones. Boosting is an approach to machine learning based on the idea of creating a highly accurate predictor by combining many weak and inaccurate “rules of thumb.” A remarkably rich theory has evolved around boosting, with connections to a range of topics, including statistics, game theory, convex optimization, and information geometry. Boosting algorithms have also enjoyed practical success in such fields as biology, vision, and speech processing. At various times in its history, boosting has been perceived as mysterious, controversial, even paradoxical. This book, written by the inventors of the method, brings together, organizes, simplifies, and substantially extends two decades of research on boosting, presenting both theory and applications in a way that is accessible to readers from diverse backgrounds while also providing an authoritative reference for advanced researchers. With its introductory treatment of all material and its inclusion of exercises in every chapter, the book is appropriate for course use as well. The book begins with a general introduction to machine learning algorithms and their analysis; then explores the core theory of boosting, especially its ability to generalize; examines some of the myriad other theoretical viewpoints that help to explain and understand boosting; provides practical extensions of boosting for more complex learning problems; and finally presents a number of advanced theoretical topics. Numerous applications and practical illustrations are offered throughout.
    Keywords: Artificial intelligence ; Algorithms and data structures ; thema EDItEUR::U Computing and Information Technology::UM Computer programming / software engineering::UMB Algorithms and data structures ; thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence::UYQM Machine learning
    Language: English
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  • 2
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    Artificial Life IX (2022)
    The MIT Press | A Bradford Book
    Details
    Publication Date: 2024-04-11
    Description: Proceedings from the ninth International Conference on Artificial Life; papers by scientists of many disciplines focusing on the principles of organization and applications of complex, life-like systems. Artificial Life is an interdisciplinary effort to investigate the fundamental properties of living systems through the simulation and synthesis of life-like processes. The young field brings a powerful set of tools to the study of how high-level behavior can arise in systems governed by simple rules of interaction. Some of the fundamental questions include: What are the principles of evolution, learning, and growth that can be understood well enough to simulate as an information process? Can robots be built faster and more cheaply by mimicking biology than by the product design process used for automobiles and airplanes? How can we unify theories from dynamical systems, game theory, evolution, computing, geophysics, and cognition? The field has contributed fundamentally to our understanding of life itself through computer models, and has led to novel solutions to complex real-world problems across high technology and human society. This elite biennial meeting has grown from a small workshop in Santa Fe to a major international conference. This ninth volume of the proceedings of the international A-life conference reflects the growing quality and impact of this interdisciplinary scientific community.
    Keywords: Artificial intelligence ; Robotics ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TJ Electronics and communications engineering::TJF Electronics engineering::TJFM Automatic control engineering::TJFM1 Robotics ; thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence::UYQM Machine learning
    Language: English
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  • 3
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    Global Fintech (2022)
    The MIT Press | MIT Connection Science & Engineering
    Details
    Publication Date: 2022-06-21
    Description: How the global financial services sector has been transformed by artificial intelligence, data science, and blockchain. Artificial intelligence, big data, blockchain, and other new technologies have upended the global financial services sector, creating opportunities for entrepreneurs and corporate innovators. Venture capitalists have helped to fund this disruption, pouring nearly $500 billion into fintech over the last five years. This book offers global perspectives on technology-fueled transformations in financial services, with contributions from a wide-ranging group of academics, industry professionals, former government officials, and current government advisors. They examine not only the struggles of rich countries to bring the old analog world into the new digital one but also the opportunities for developing countries to “leapfrog” directly into digital. The book offers accessible explanations of blockchain and distributed ledger technology and explores big data analytics. It considers, among other things, open banking, platform-based strategies for banks, and digital financial services. Case studies imagine possible future fintech-government interaction, emphasizing that legal and regulatory frameworks can help to create trust in financial processes. The contributors offer novel takes and unexpected insights that will be of interest to fintech experts and nonexperts alike. Contributors Ajay Bhalla, Michelle Chivunga, John D'Agostino, Mark Flood, Amias Moore Gerety, Oliver R. Goodenough, Thomas Hardjono, Sharmila Kassam, Boris Khentov, Alexander Lipton, Lev Menand, Pinar Ozcan, Alex Pentland, Matthew Reed, David L. Shrier, Markos Zachariadis
    Keywords: Finance ; E-commerce: business aspects ; Artificial intelligence ; bic Book Industry Communication::K Economics, finance, business & management::KF Finance & accounting::KFF Finance::KFFL Credit & credit institutions ; bic Book Industry Communication::K Economics, finance, business & management::KJ Business & management::KJE E-commerce: business aspects ; bic Book Industry Communication::U Computing & information technology::UY Computer science::UYQ Artificial intelligence::UYQM Machine learning
    Language: English
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  • 4
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    Data Paradoxes (2023)
    The MIT Press | The MIT Press
    Details
    Publication Date: 2024-04-14
    Description: Why healthcare cannot—and should not—become data-driven, despite the many promises of intensified data sourcing.In contemporary healthcare, everybody seems to want more data, of higher quality, on more people, and to use this data for a wider range of purposes. In theory, such pervasive data collection should lead to a healthcare system in which data can quickly, efficiently, and unambiguously be interpreted and provide better care for patients, more efficient administration, enhanced options for research, and accelerated economic growth. In practice, however, data are difficult to interpret and the many purposes often undermine one another. In this book, anthropologist and STS scholar Klaus Hoeyer offers an in-depth look at the paradoxes surrounding healthcare data.Focusing on Denmark, a world leader in healthcare data infrastructures, Hoeyer shares the perspectives of different stakeholders, from epidemiologists to hospital managers, from patients to physicians, analyzing the social dynamics set in motion by data intensification and calling special attention to that which cannot be easily coded in a database. He illustrates how data can be at once helpful, overwhelming, and sometimes disastrous through concrete examples. The COVID-19 pandemic serves as a special closing case study that shows how these data paradoxes carry weighty political implications. By revealing the diverse and sometimes contradictory practices spawned by intensified data sourcing, Data Paradoxes raises vital questions about how we might better use healthcare data.
    Keywords: Data ; datafication ; data work ; data sharing ; data infrastructures ; information infrastructures ; Digital health ; eHealth ; Artificial intelligence ; AI ; algorithms ; automation ; Health ; health care, healthcare ; hospitals ; medicine ; Data politics ; data mining ; intensified data sourcing ; data-based management ; learning healthcare systems ; personalized medicine ; real-world data ; real-world evidence ; Denmark ; Scandinavia ; European Union, EU ; Global North ; Science and technology studies ; science, technology and society ; STS ; anthropology ; medical anthropology ; sociology ; medical sociology ; data studies ; critical data studies ; thema EDItEUR::U Computing and Information Technology::UY Computer science
    Language: English
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  • 5
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    Artificial Life VII (2022)
    The MIT Press | A Bradford Book
    Details
    Publication Date: 2024-04-14
    Description: The term "artificial life" describes research into synthetic systems that possess some of the essential properties of life. This interdisciplinary field includes biologists, computer scientists, physicists, chemists, geneticists, and others. Artificial life may be viewed as an attempt to understand high-level behavior from low-level rules—for example, how the simple interactions between ants and their environment lead to complex trail-following behavior. An understanding of such relationships in particular systems can suggest novel solutions to complex real-world problems such as disease prevention, stock-market prediction, and data mining on the Internet. Since their inception in 1987, the Artificial Life meetings have grown from small workshops to truly international conferences, reflecting the field's increasing appeal to researchers in all areas of science.
    Keywords: Artificial intelligence ; thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence::UYQM Machine learning
    Language: English
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  • 6
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    Artificial Communication (2022)
    The MIT Press | The MIT Press
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    Publication Date: 2022-06-21
    Description: A proposal that we think about digital technologies such as machine learning not in terms of artificial intelligence but as artificial communication. Algorithms that work with deep learning and big data are getting so much better at doing so many things that it makes us uncomfortable. How can a device know what our favorite songs are, or what we should write in an email? Have machines become too smart? In Artificial Communication, Elena Esposito argues that drawing this sort of analogy between algorithms and human intelligence is misleading. If machines contribute to social intelligence, it will not be because they have learned how to think like us but because we have learned how to communicate with them. Esposito proposes that we think of “smart” machines not in terms of artificial intelligence but in terms of artificial communication. To do this, we need a concept of communication that can take into account the possibility that a communication partner may be not a human being but an algorithm—which is not random and is completely controlled, although not by the processes of the human mind. Esposito investigates this by examining the use of algorithms in different areas of social life. She explores the proliferation of lists (and lists of lists) online, explaining that the web works on the basis of lists to produce further lists; the use of visualization; digital profiling and algorithmic individualization, which personalize a mass medium with playlists and recommendations; and the implications of the “right to be forgotten.” Finally, she considers how photographs today seem to be used to escape the present rather than to preserve a memory.
    Keywords: Media studies ; Artificial intelligence ; Algorithms and data structures ; bic Book Industry Communication::J Society & social sciences::JF Society & culture: general::JFD Media studies::JFDV Advertising & society ; bic Book Industry Communication::U Computing & information technology::UY Computer science::UYQ Artificial intelligence::UYQM Machine learning ; bic Book Industry Communication::U Computing & information technology::UM Computer programming / software development::UMB Algorithms & data structures
    Language: English
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  • 7
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    Against Reduction (2022)
    The MIT Press | The MIT Press
    Details
    Publication Date: 2024-04-14
    Description: Provocative, hopeful essays imagine a future that is not reduced to algorithms. What is human flourishing in an age of machine intelligence, when many claim that the world's most complex problems can be reduced to narrow technical questions? Does more computing make us more intelligent, or simply more computationally powerful? We need not always resist reduction; our ability to simplify helps us interpret complicated situations. The trick is to know when and how to do so. Against Reduction offers a collection of provocative and illuminating essays that consider different ways of recognizing and addressing the reduction in our approach to artificial intelligence, and ultimately to ourselves. Inspired by a widely read manifesto by Joi Ito that called for embracing the diversity and irreducibility of the world, these essays offer persuasive and compelling variations on resisting reduction. Among other things, the writers draw on Indigenous epistemology to argue for an extended “circle of relationships” that includes the nonhuman and robotic; cast “Snow White” as a tale of AI featuring a smart mirror; point out the cisnormativity of security protocol algorithms; map the interconnecting networks of so-called noncommunicable disease; and consider the limits of moral mathematics. Taken together, they show that we should push back against some of the reduction around us and do whatever is in our power to work toward broader solutions.
    Keywords: Artificial intelligence ; Impact of science and technology on society ; thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence::UYQM Machine learning ; thema EDItEUR::P Mathematics and Science::PD Science: general issues::PDR Impact of science and technology on society
    Language: English
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  • 8
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    Gaussian Processes for Machine Learning (2022)
    The MIT Press | The MIT Press
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    Publication Date: 2024-04-14
    Description: A comprehensive and self-contained introduction to Gaussian processes, which provide a principled, practical, probabilistic approach to learning in kernel machines. Gaussian processes (GPs) provide a principled, practical, probabilistic approach to learning in kernel machines. GPs have received increased attention in the machine-learning community over the past decade, and this book provides a long-needed systematic and unified treatment of theoretical and practical aspects of GPs in machine learning. The treatment is comprehensive and self-contained, targeted at researchers and students in machine learning and applied statistics. The book deals with the supervised-learning problem for both regression and classification, and includes detailed algorithms. A wide variety of covariance (kernel) functions are presented and their properties discussed. Model selection is discussed both from a Bayesian and a classical perspective. Many connections to other well-known techniques from machine learning and statistics are discussed, including support-vector machines, neural networks, splines, regularization networks, relevance vector machines and others. Theoretical issues including learning curves and the PAC-Bayesian framework are treated, and several approximation methods for learning with large datasets are discussed. The book contains illustrative examples and exercises, and code and datasets are available on the Web. Appendixes provide mathematical background and a discussion of Gaussian Markov processes.
    Keywords: Computer science ; Artificial intelligence ; thema EDItEUR::U Computing and Information Technology::UY Computer science ; thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence::UYQM Machine learning
    Language: English
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  • 9
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    Frankenstein (2022)
    The MIT Press | The MIT Press
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    Publication Date: 2024-03-27
    Description: The original 1818 text of Mary Shelley's classic novel, with annotations and essays highlighting its scientific, ethical, and cautionary aspects. Mary Shelley's Frankenstein has endured in the popular imagination for two hundred years. Begun as a ghost story by an intellectually and socially precocious eighteen-year-old author during a cold and rainy summer on the shores of Lake Geneva, the dramatic tale of Victor Frankenstein and his stitched-together creature can be read as the ultimate parable of scientific hubris. Victor, “the modern Prometheus,” tried to do what he perhaps should have left to Nature: create life. Although the novel is most often discussed in literary-historical terms—as a seminal example of romanticism or as a groundbreaking early work of science fiction—Mary Shelley was keenly aware of contemporary scientific developments and incorporated them into her story. In our era of synthetic biology, artificial intelligence, robotics, and climate engineering, this edition of Frankenstein will resonate forcefully for readers with a background or interest in science and engineering, and anyone intrigued by the fundamental questions of creativity and responsibility. This edition of Frankenstein pairs the original 1818 version of the manuscript—meticulously line-edited and amended by Charles E. Robinson, one of the world's preeminent authorities on the text—with annotations and essays by leading scholars exploring the social and ethical aspects of scientific creativity raised by this remarkable story. The result is a unique and accessible edition of one of the most thought-provoking and influential novels ever written. Essays by Elizabeth Bear, Cory Doctorow, Heather E. Douglas, Josephine Johnston, Kate MacCord, Jane Maienschein, Anne K. Mellor, Alfred Nordmann
    Keywords: science fiction ; gothic ; horror ; European ; British ; literature ; fiction ; cautionary tale ; STEM ; science ; bioethics ; classic ; bicentennial ; Josephine Johnston ; Cory Doctorow ; Jane Maienschein ; Kate MacCord ; Alfred Nordmann ; Elizabeth Bear ; Anne K. Mellor ; Heather E. Douglas ; Frankenstein ; Creature ; Monster ; Mary Shelley ; Makers ; women in science ; science and anti-science ; values in science ; responsible innovation ; Industrial Revolution ; Mary Wollstonecraft ; William Godwin ; Percy Bysshe Shelley ; Galvanism ; Mount Tambora ; Myths ; Two Cultures ; epistolary novel ; Victor Frankenstein ; Geneva ; Prometheus ; Arctic ; Lord Byron ; John Polidori ; ghost stories ; Revisions ; Electricity ; Lightning ; Vitalism ; Chemistry ; Extinction ; Magnetism ; Moral responsibility ; Legal responsibility ; Social responsibility ; Consequences ; Obligations ; Ethics ; Maker Culture ; DIY ; Technology Adjacent Possible ; Facebook ; Surveillance ; Aristotle ; Fetal development ; Epigenesis ; Embryo ; Person ; Technoscience ; Alchemy ; uncanny valley ; animation ; complexity ; Morality ; Monstrosity ; Christianity ; Otherness ; Gender ; Nature ; Domestic Affections ; Women ; Sexuality ; Technical Sweetness ; Los Alamos ; Trinity Test ; Scientific Responsibility ; Nuclear Weapons ; adjacent possible ; synthetic biology ; robotics ; thema EDItEUR::F Fiction and Related items::FB Fiction: general and literary::FBC Classic fiction: general and literary ; thema EDItEUR::F Fiction and Related items::FL Science fiction::FLC Classic science fiction
    Language: English
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