18 research outputs found

    A Behavioral Model of Component Frameworks

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    When using a component framework developers need to respect the behavior implemented by the components. Static information about the component interface is not sufficient. Dynamic information such as the description of valid sequences of operations is required. Instead of being in some external documentation, this information should be formally represented and embedded within the components themselves, so that it can be used by automatic tools. We propose a mathematical model and a formal language to describe the knowledge about behavior. We rely on a hierarchical model of deterministic finite state-machines. The communication between the machines follows the Synchronous Paradigm. We favor a structural approach allowing incremental simulation, automatic verification, code generation, and run-time checks. Associated tools may ensure correct and safe reuse of the components. We focus on extension of components through inheritance (in the sense of sub-typing), owing to the notion of behavioral refinement

    Statistical approaches for natural language modelling and monotone statistical machine translation

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    Esta tesis reune algunas contribuciones al reconocimiento de formas estadístico y, más especícamente, a varias tareas del procesamiento del lenguaje natural. Varias técnicas estadísticas bien conocidas se revisan en esta tesis, a saber: estimación paramétrica, diseño de la función de pérdida y modelado estadístico. Estas técnicas se aplican a varias tareas del procesamiento del lenguajes natural tales como clasicación de documentos, modelado del lenguaje natural y traducción automática estadística. En relación con la estimación paramétrica, abordamos el problema del suavizado proponiendo una nueva técnica de estimación por máxima verosimilitud con dominio restringido (CDMLEa ). La técnica CDMLE evita la necesidad de la etapa de suavizado que propicia la pérdida de las propiedades del estimador máximo verosímil. Esta técnica se aplica a clasicación de documentos mediante el clasificador Naive Bayes. Más tarde, la técnica CDMLE se extiende a la estimación por máxima verosimilitud por leaving-one-out aplicandola al suavizado de modelos de lenguaje. Los resultados obtenidos en varias tareas de modelado del lenguaje natural, muestran una mejora en términos de perplejidad. En a la función de pérdida, se estudia cuidadosamente el diseño de funciones de pérdida diferentes a la 0-1. El estudio se centra en aquellas funciones de pérdida que reteniendo una complejidad de decodificación similar a la función 0-1, proporcionan una mayor flexibilidad. Analizamos y presentamos varias funciones de pérdida en varias tareas de traducción automática y con varios modelos de traducción. También, analizamos algunas reglas de traducción que destacan por causas prácticas tales como la regla de traducción directa; y, así mismo, profundizamos en la comprensión de los modelos log-lineares, que son de hecho, casos particulares de funciones de pérdida. Finalmente, se proponen varios modelos de traducción monótonos basados en técnicas de modelado estadístico .Andrés Ferrer, J. (2010). Statistical approaches for natural language modelling and monotone statistical machine translation [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/7109Palanci

    Energy-Performance Optimization for the Cloud

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    Exponential Family Predictive Representations of State.

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    Many agent-environment interactions can be framed as dynamical systems in which agents take actions and receive observations. These dynamical systems are diverse, representing such things as a biped walking, a stock price changing over time, the trajectory of a missile, or the shifting fish population in a lake. Often, interacting successfully with the environment requires the use of a model, which allows the agent to predict something about the future by summarizing the past. Two of the basic problems in modeling partially observable dynamical systems are selecting a representation of state and selecting a mechanism for maintaining that state. This thesis explores both problems from a learning perspective: we are interested in learning a predictive model directly from the data that arises as an agent interacts with its environment. This thesis develops models for dynamical systems which represent state as a set of statistics about the short-term future, as opposed to treating state as a latent, unobservable quantity. In other words, the agent summarizes the past into predictions about the short-term future, which allow the agent to make further predictions about the infinite future. Because all parameters in the model are defined using only observable quantities, the learning algorithms for such models are often straightforward and have attractive theoretical properties. We examine in depth the case where state is represented as the parameters of an exponential family distribution over a short-term window of future observations. We unify a number of different existing models under this umbrella, and predict and analyze new models derived from the generalization. One goal of this research is to push models with predictively defined state towards real-world applications. We contribute models and companion learning algorithms for domains with partial observability, continuous observations, structured observations, high-dimensional observations, and/or continuous actions. Our models successfully capture standard POMDPs and benchmark nonlinear timeseries problems with performance comparable to state-of-the-art models. They also allow us to perform well on novel domains which are larger than those captured by other models with predictively defined state, including traffic prediction problems and domains analogous to autonomous mobile robots with camera sensors.Ph.D.Computer Science & EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/58522/1/wingated_1.pd

    NASA university program management information system, FY 1994

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    The University Program report, Fiscal Year 1994, provides current information and related statistics for 7841 grants/contracts/cooperative agreements active during the reporting period. NASA field centers and certain Headquarters program offices provide funds for those activities in universities which contribute to the mission needs of that particular NASA element. This annual report is one means of documenting the NASA-university relationship, frequently denoted, collectively, as NASA's University Program

    NASA University Program Management Information System: FY 1995

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    The University Program Report, Fiscal Year 1995, provides current information and related statistics for grants/contracts/cooperative agreements active during the report period. NASA field centers and certain Headquarters program offices provide funds for those R&D activities in universities which contribute to the mission needs of that particular NASA element. This annual report is one means of documenting the NASA-university relationship, frequently denoted, collectively, as NASA's University Program

    NASA university program management information system, FY 1985

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    The University Program Report provides current information and related statistics for approximately 4200 grants/contracts/cooperative agreements active during the reporting period. NASA Field Centers and certain Headquarters Program Offices provide funds for those research and development activities in universities which contribute to the mission needs of that particular NASA element. This annual report is one means of documenting the NASA-University relationship, frequently denoted, collectively, as NASA's University Program
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