Xem 1-20 trên 409 kết quả Theoretical models
  • This paper presents empirical studies and closely corresponding theoretical models of the performance of a chart parser exhaustively parsing the Penn Treebank with the Treebank’s own CFG grammar. We show how performance is dramatically affected by rule representation and tree transformations, but little by top-down vs. bottom-up strategies.

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  • We present a game-theoretic model of bargaining over a metaphor in the context of political communication, find its equilibrium, and use it to rationalize observed linguistic behavior. We argue that game theory is well suited for modeling discourse as a dynamic resulting from a number of conflicting pressures, and suggest applications of interest to computational linguists.

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  • This book is about how to construct and use computational models of specific parts of the nervous system, such as a neuron, a part of a neuron or a network of neurons. It is designed to be read by people from a wide range of backgrounds from the biological, physical and computational sciences. The word ‘model’ can mean different things in different disciplines, and even researchers in the same field may disagree on the nuances of its meaning.

    pdf0p taurus23 27-09-2012 19 3   Download

  • Health and Quality of Life Outcomes BioMed Central Review Open Access Toward a theoretical model of quality-of-life appraisal: Implications of findings from studies of response shift Bruce D Rapkin*1 and Carolyn E Schwartz2,3,4,5 Address: 1Department of Psychiatry and the Behavioral Sciences, Memorial Sloan Kettering Cancer Center, New York, NY, USA, 2QualityMetric Incorporated, Waltham, MA, USA, 3Health Assessment Lab, Waltham, MA, USA, 4Division of Preventive and Behavioral Medicine, Department of Medicine, University of Massachusetts Medical School, Worcester, MA, USA and 5DeltaQuest ...

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  • This book aims to give a complete and self-contained presentation of semi- Markov models with finitely many states, in view of solving real life problems of risk management in three main fields: Finance, Insurance and Reliability providing a useful complement to our first book (Janssen and Manca (2006)) which gives a theoretical presentation of semi-Markov theory. However, to help assure the book is self-contained, the first three chapters provide a summary of the basic tools on semi-Markov theory that the reader will need to understand our presentation.

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  • The second edition of "Model Predictive Control" provides a thorough introduction to theoretical and practical aspects of the most commonly used MPC strategies. It bridges the gap between the powerful but often abstract techniques of control researchers and the more empirical approach of practitioners. The book demonstrates that a powerful technique does not always require complex control algorithms. Many new exercises and examples have also been added throughout.

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  • Hidden Markov Models (HMMs), although known for decades, have made a big career nowadays and are still in state of development. This book presents theoretical issues and a variety of HMMs applications in speech recognition and synthesis, medicine, neurosciences, computational biology, bioinformatics, seismology, environment protection and engineering. I hope that the reader will find this book useful and helpful for their own research.

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  • With the amazing advances of scientific research, Hydrodynamics - Theory and Application presents the engineering applications of hydrodynamics from many countries around the world. A wide range of topics are covered in this book, including the theoretical, experimental, and numerical investigations on various subjects related to hydrodynamic problems. The book consists of twelve chapters, each of which is edited separately and deals with a specific topic. The book is intended to be a useful reference to the readers who are working in this field....

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  • This book was conceived as a result of many years research with students and postdocs in molecular simulation, and shaped over several courses on the subject given at the University of Groningen, the Eidgen¨ossische Technische Hochschule (ETH) in Z¨urich, the University of Cambridge, UK, the University of Rome (La Sapienza), and the University of North Carolina at Chapel Hill, NC, USA.

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  • Understanding and quantitative describing of marine ecosystems requires an integration of physics, chemistry and biology. The coupling between physics, which regulates for example nutrient availability and the physical position of many organisms is particularly important and thus cannot be described by biology alone. Therefore the appropriate basis for theoretical investigations of marine systems are coupled models, which integrate physical, chemical and biological interactions.

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  • This book addresses the stochastic modeling of telecommunication networks, introducing the main mathematical tools for that purpose, such as Markov processes, real and spatial point processes and stochastic recursions, and presenting a wide list of results on stability, performances and comparison of systems. The authors propose a comprehensive mathematical construction of the foundations of stochastic network theory: Markov chains, continuous time Markov chains are extensively studied using an original martingale-based approach.

    pdf385p titatu_123 01-03-2013 21 8   Download

  • This is the fourth edition of Professor Lindauer's early ground-breaking Macroeconomics series. It holds reader interest because it constantly relates the concepts of modern macroeconomics to today's "Great Recession" and the policies and conditions that brought it about and are needed to end it. In so doing it explains why not all Keynesian and neo-classical theory and monetary and fiscal policies are applicable to the unique structure and institutions of the United States and how the current recession can be quickly ended -...

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  • Mathematical modelling is the process of formulating an abstract model in terms of mathematical language to describe the complex behaviour of a real system. Mathematical models are quantitative models and often expressed in terms of ordinary differential equations and partial differential equations. Mathematical models can also be statistical models, fuzzy logic models and empirical relationships. In fact, any model description using mathematical language can be called a mathematical model.

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  • Mathematical Finance is themathematical theory of financialmarkets. It tries to develop theoretical models, that can be used by “practitioners” to evaluate certain data from “real” financial markets. A model cannot be “right” or wrong, it can only be good or bad ( for practical use ). Even “bad” models can be “good” for theoretical insight.

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  • Earnings occupy a central position in accounting. It is accounting's summary measure of a firm's performance. Despite theoretical models that value cash flows, accounting earnings is widely used in share valuation and to measure performance in management and debt contracts. Various explanations have been advanced to explain the prominence of accounting earnings and the reasons for its usage. An example is that earnings reflects cash flow forecasts (e.g., Beaver, 1989, p. 98; and Dechow, 1994) and has a higher correlation with value than current does cash flow (e.g.

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  • We investigate the relevance of hierarchical topic models to represent the content of Web gists. We focus our attention on DMOZ, a popular Web directory, and propose two algorithms to infer such a model from its manually-curated hierarchy of categories. Our first approach, based on information-theoretic grounds, uses an algorithm similar to recursive feature selection. Our second approach is fully Bayesian and derived from the more general model, hierarchical LDA.

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  • The PageRank algorithm, used in the Google search engine, greatly improves the results of Web search by applying probabilistic model on the link structure of Webs to evaluate the “importance” of Webs. In PageRank probabilistic model, the links and webs are uniform, so the rank score of webs are quite independent from their content. In practice, the researchers often hope that the web results can be ranked by their proposed topics. Moreover, when computer’s techniques solve given problems ineffectively, it’s necessary to do better research in theoretical problems. ...

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  • We describe a new loss function, due to Jeon and Lin (2006), for estimating structured log-linear models on arbitrary features. The loss function can be seen as a (generative) alternative to maximum likelihood estimation with an interesting information-theoretic interpretation, and it is statistically consistent. It is substantially faster than maximum (conditional) likelihood estimation of conditional random fields (Lafferty et al., 2001; an order of magnitude or more).

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  • A natural next step in the evolution of constraint-based grammar formalisms from rewriting formalisms is to abstract fully away from the details of the grammar mechanism--to express syntactic theories purely in terms of the properties of the class of structures they license.

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  • Model-theoretic semantics provides a computationally attractive means of representing the semantics of natural language. However, the models used in this formalism are static and are usually infinite. Dynamic models are incomplete models that include only the information needed for an application and to which information can be added. Dynamic models are basically approximations of larger conventional models, but differ is several interesting ways. The difference discussed here is the possibility of inconsistent information being included in the model. ...

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