Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 18 of 18 for “"graphical modeling"”.
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Probabilistic Graphical Modeling on Big Data
… challenges to modern statistical analysis and modeling. In toxicogenomics, the advancement of high-throughput screening technologies facilitates the generation of massive amount of biological data, a big data phenomena in biomedical science. Yet, researchers still heavily rely on key word …
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Variable screening and graphical modeling for ultra-high dimensional longitudinal data
… explore the relationship among the variables. Graphical models are commonly used to explore the association network for a set of variables, which could be genes or other objects under study. However, graphical modes currently used are only designed for single replicate data, rather than …
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Energy-efficient information inference in wireless sensor networks based on graphical modeling
… a systematic approach, based on a probabilistic graphical model, to infer missing observations in wireless sensor networks (WSNs) for sustaining environmental monitoring. This enables us to effectively address two critical challenges in WSNs: (1) energy-efficient data gathering through planned …
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Methods and Theory for Nonparametric Inference In High-dimensional Settings
… estimation and inference problems of graphical modeling, linear association assessment, and matrix completion. First, we introduce a flexible framework for nonparametric graphical modeling. We propose three nonparametric measures of conditional dependence, which have theoretically …
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An Approach for Fast Score Computation in Bayesian Network Structure Learning Over Large-Scale Distributed Data
… has lead to its employment in probabilistic graphical modeling and the inception of Bayesian networks. The field is saturated with techniques to learn the structure of a Bayesian network (also known as Bayes network). Nevertheless, most of the techniques struggle when the number of variables …
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Mining latent entity structures from massive unstructured and interconnected data
… such as advisor-advisee. A probabilistic graphical modeling approach is proposed. The method can utilize heterogeneous attributes and links to capture all kinds of semantic signals, including constraints and dependencies, to recover the hierarchical relationship with the best known …
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Desiree - a Refinement Calculus for Requirements Engineering
… The framework also includes an ontology for modeling and classifying requirements, a description-based language for representing requirements, as well as a systematic method for applying the concepts and operators in order to engineer an eligible specification from stakeholder requirements. …
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Efficient Machine Learning with High Order and Combinatorial Structures
… the learning methods necessary for the accurate modeling of domains that exhibit complex and non-local dependency structures. There are three parts to this thesis. In the first part, we develop a toolbox of high order potentials (HOPs) that are useful for defining interactions and constraints …
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Composable probabilistic inference with BLAISE
… a novel framework for composable probabilistic modeling and inference, designed to address these limitations. BLAISE has three components: * The BLAISE State-Density-Kernel (SDK) graphical modeling language that generalizes factor graphs by: (1) explicitly representing inference algorithms (and …
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Graphical model driven methods in adaptive system identification
… statistical structure on the input. By modeling the input to the system of interest as a graph-structured random process, it is shown that a large parameter identification problem can be reduced into several smaller pieces, making the overall problem considerably simpler. Algorithms that …
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Estimation of GMRFs by recursive cavity modeling
… develops the novel method of recursive cavity modeling as a tractable approach to approximate inference in large Gauss-Markov random fields. The main idea is to recursively dissect the field, constructing a cavity model for each subfield at each level of dissection. The cavity model provides a …
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DSP centered modular building blocks and object-oriented modeling for power electronic systems
… is an object-oriented simulation approach for modeling and designing power electronic systems using the simulator DYMOLA. This software approach also provides for a virtual state-of-the-art power electronics laboratory where a circuit of any complexity can be quickly modeled simulated and …
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Integrated Design and Manufacturing [IDM] Framework for the Modular Construction Industry
… The Integration Definition (IDEF0) for Function Modeling was used as a graphical presentation technique. The goal of using such a graphical technique was, first, to understand and analyze the functions of the existing "As-is" design-manufacture communication process; and second, to enhance and …
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Combat System Modeling:Modeling Large-Scale Software and Hardware Application Using UML
… in an easy to understand manner. The Unified Modeling Language (UML), an Object Management Group's (OMG) standard, is a graphical modeling language used for specifying, visualizing, constructing, and documenting software intensive artifacts. UML, which has been accepted as an industry standard …
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Behavior and confluence analysis of M-adhesive transformation systems using M-functors
For modeling dynamic systems, various graphical modeling formalisms exist. In particular, rule-based graph transformation formalisms have proven to be adequate, both to capture system behavior and system adaptations. For some graph transformation-based formalisms there already exist …
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Analyzing information flow in social networks for knowledge discovery
In the last few years the online world has seen a surge in users’ social behavior. No longer is the image of a lone user surfing the web relevant anymore and with social sites such as Facebook, Twitter, etc. online users can now actively interact with other users. It is now quite common for web …
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Graphical models for student knowledge: Networks, parameters, and item selection
… are concepts within the larger field of `X'). Graphical modeling (e.g., Bayesian networks and structural equation models) provides a convenient and intuitive way to represent and model these structural relationships explicitly. This dissertation investigates the use of graphical knowledge …
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Graphical SLAM for urban UAV navigation
… improve urban GPS, one approach uses environment modeling such as 3D city models to mitigate the effects of multipath and NLOS errors. Others pair GPS with odometry measurements from relative positioning sensors, such as Light Detection and Ranging (LiDAR) sensors. LiDAR-based odometry provides an …