Mit press jul 2009 (2 Ergebnisse)

Taschenbuch. Zustand: Neu. Neuware - Drawings, doodles, and ideograms argue with ferocity and wit for traditional urbanism and architecture.Architect Léon Krier's doodles, drawings, and ideograms make arguments in images, without the circumlocutions of prose. Drawn with wit and grace, these clever sketches do not try to please or flatter the architectural establishment. Rather, they make an impassioned argument against what Krier sees as the unquestioned doctrines and unacknowledged absurdities of contemporary architecture. Thus he shows us a building bearing a suspicious resemblance to Norman Foster's famous London "gherkin" as an example of "priapus hubris" (threatened by detumescence and "priapus nemesis"); he charts "Random Uniformity" ("fake simplicity") and "Uniform Randomness" ("fake complexity"); he draws bloated "bulimic" and disproportionately scrawny "anorexic" columns flanking a graceful "classical" one; and he compares "private virtue" (modernist architects' homes and offices) to "public vice" (modernist architects' "creations"). Krier wants these witty images to be tools for re-founding traditional urbanism and architecture. He argues for mixed-use cities, of "architectural speech" rather than "architectural stutter," and pointedly plots the man-vehicle-landneed ratio of "sub-urban man" versus that of a city dweller. In an age of energy crisis, he writes (and his drawings show), we "build in the wrong places, in the wrong patterns, materials, densities, and heights, and for the wrong number of dwellers"; a return to traditional architectures and building and settlement techniques can be the means of ecological reconstruction. Each of Krier's provocative and entertaining images is worth more than a thousand words of theoretical abstraction.…

Buch. Zustand: Neu. Neuware - A general framework for constructing and using probabilistic models of complex systems that would enable a computer to use available information for making decisions.Most tasks require a person or an automated system to reason to reach conclusions based on available information. The framework of probabilistic graphical models, presented in this book, provides a general approach for this task. The approach is model-based, allowing interpretable models to be constructed and then manipulated by reasoning algorithms. These models can also be learned automatically from data, allowing the approach to be used in cases where manually constructing a model is difficult or even impossible. Because uncertainty is an inescapable aspect of most real-world applications, the book focuses on probabilistic models, which make the uncertainty explicit and provide models that are more faithful to reality. Probabilistic Graphical Models discusses a variety of models, spanning Bayesian networks, undirected Markov networks, discrete and continuous models, and extensions to deal with dynamical systems and relational data. For each class of models, the text describes the three fundamental cornerstones: representation, inference, and learning, presenting both basic concepts and advanced techniques. Finally, the book considers the use of the proposed framework for causal reasoning and decision making under uncertainty. The main text in each chapter provides the detailed technical development of the key ideas. Most chapters also include boxes with additional material: skill boxes, which describe techniques; case study boxes, which discuss empirical cases related to the approach described in the text, including applications in computer vision, robotics, natural language understanding, and computational biology; and concept boxes, which present significant concepts drawn from the material in the chapter. Instructors (and readers) can group chapters in various combinations, from core topics to more technically advanced material, to suit their particular needs.…