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Este volumen es producto de una confluencia de experiencias historiográficas heterogéneas, forjadas en la práctica de la historia política, la historia religiosa y la historia conceptual desde diversos puntos de la geografía latinoamericana y reunidas en el grupo de trabajo, Religión y política, de la red Iberconceptos de historia conceptual comparada. Ofrece un acercamiento a la forma en que la producción histórica de campos diferenciados para lo político y lo religioso tuvo lugar en el lenguaje y, a través de éste, en las prácticas, instituciones y relaciones políticas. Está constituido por textos centrados en trayectorias semánticas específicas, estrechamente ligadas entr...
This is the first textbook on pattern recognition to present the Bayesian viewpoint. The book presents approximate inference algorithms that permit fast approximate answers in situations where exact answers are not feasible. It uses graphical models to describe probability distributions when no other books apply graphical models to machine learning. No previous knowledge of pattern recognition or machine learning concepts is assumed. Familiarity with multivariate calculus and basic linear algebra is required, and some experience in the use of probabilities would be helpful though not essential as the book includes a self-contained introduction to basic probability theory.
This book constitutes the thoroughly refereed post-conference proceedings of the 8th International Conference on Fundamentals of Software Engineering, FSEN 2019, held in Tehran, Iran, in May 2019. The 14 full papers and 3 short papers presented in this volume were carefully reviewed and selected from 47 submissions. The topics of interest in FSEN span over all aspects of formal methods, especially those related to advancing the application of formal methods in the software industry and promoting their integration with practical engineering techniques. The papers are organized in topical sections on agent based systems, theorem proving, learning, verification, distributed algorithms, and program analysis.
The significantly expanded and updated new edition of a widely used text on reinforcement learning, one of the most active research areas in artificial intelligence. Reinforcement learning, one of the most active research areas in artificial intelligence, is a computational approach to learning whereby an agent tries to maximize the total amount of reward it receives while interacting with a complex, uncertain environment. In Reinforcement Learning, Richard Sutton and Andrew Barto provide a clear and simple account of the field's key ideas and algorithms. This second edition has been significantly expanded and updated, presenting new topics and updating coverage of other topics. Like the fir...
Class-tested and coherent, this textbook teaches classical and web information retrieval, including web search and the related areas of text classification and text clustering from basic concepts. It gives an up-to-date treatment of all aspects of the design and implementation of systems for gathering, indexing, and searching documents; methods for evaluating systems; and an introduction to the use of machine learning methods on text collections. All the important ideas are explained using examples and figures, making it perfect for introductory courses in information retrieval for advanced undergraduates and graduate students in computer science. Based on feedback from extensive classroom experience, the book has been carefully structured in order to make teaching more natural and effective. Slides and additional exercises (with solutions for lecturers) are also available through the book's supporting website to help course instructors prepare their lectures.
Judicial Reforms in Mexico
The first of its kind, this reference gives a comprehensive but concise introduction to epigenetics before covering the many interactions between hormone regulation and epigenetics at all levels. The contents are very well structured with no overlaps between chapters, and each one features supplementary material for use in presentations. Throughout, major emphasis is placed on pathological conditions, aiming at the many physiologists and developmental biologists who are familiar with the importance and mechanisms of hormone regulation but have a limited background in epigenetics.
The use of non-Saccharomyces yeast species is currently a biotechnology trend in enology for which they are being broadly used to improve the sensory profile of wines because they affect aroma, color, and mouthfeel. They have become a powerful biotool to modulate the influence of global warming on grape varieties, helping to maintain the acidity, decrease the alcoholic degree, stabilize wine color, and increase freshness. In cool climates, some non-Saccharomyces can promote demalication or color stability by the formation of stable derived pigments. Additionally, non-Saccharomyces yeasts open new possibilities in biocontrol for removing spoilage yeast and bacteria or molds that can produce and release mycotoxins and, thereby, help in reducing applied SO2 levels.
This book offers a comprehensive synthesis of over 40 years of research on models in physical education to suggest Models-based Practice (MbP) as an innovative future approach to physical education. It lays out the ideal conditions for MbP to flourish by situating pedagogical models at the core of physical education programs and allowing space for local agency and the co-construction of practice. Starting from the premise that true MbP does not yet exist, the book makes a case for the term "pedagogical model" over alternatives such as curriculum model and instructional model, and explains how learners’ cognitive, social, affective and psychomotor needs should be organised in ways that are ...