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 20 of 31 for “"Probabilistic Reasoning"”.
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Probabilistic reasoning and inference for systems biology
… the important challenges in Systems Biology is reasoning and performing hypotheses testing in uncertain conditions, when available knowledge may be incomplete and the experimental data may contain substantial noise. In this thesis we develop methods of probabilistic reasoning and inference that …
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A probabilistic reasoning-based approach to machine learning
… learning, based on the principle of learning by reasoning. Current learning systems have significant limitations like brittleness, i.e. the deterioration of performance on a different domain or problem and lack of power required for handling real-world learning problems. The goal of my research …
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Probing the Probabilistic Reasoning and Belief Change Abilities of Preschool-Age Children
… about how children might use self-selected, probabilistic evidence to revise their beliefs over time. The current study investigated the ability of 3- to 5-year-old children to revise their beliefs on a novel ‘fishing’ game. Thirty-two children were induced with a belief about which of two …
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Adult age differences in thinking styles and probabilistic reasoning : the effect of natural frequencies
Probabilistic reasoning is a distinct type of reasoning which previous evidence has found to be particularly difficult for both naive and expert participants in laboratory research. The current study looked at probabilistic reasoning performance in the light of dual- process theories of thinking …
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Bayesian Probabilistic Reasoning Applied to Mathematical Epidemiology for Predictive Spatiotemporal Analysis of Infectious Diseases
Abstract Probabilistic reasoning under uncertainty suits well to analysis of disease dynamics. The stochastic nature of disease progression is modeled by applying the principles of Bayesian learning. Bayesian learning predicts the disease progression, including prevalence and incidence, for a …
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CAPRI : a common architecture for distributed probabilistic Internet fault diagnosis
… the Internet based on a Common Architecture for Probabilistic Reasoning in the Internet (CAPRI) in which distributed, heterogeneous diagnostic agents efficiently conduct diagnostic tests and communicate observations, beliefs, and knowledge to probabilistically infer the cause of network failures. …
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A Framework for Combining Logical and Probabilistic Models
… expressive power of first-order logic with the probabilistic reasoning power of Bayesian networks has attracted the interest of many researchers. We review many techniques for integration of first-order logic and Bayesian networks and propose a new framework that exploits the translation of …
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Provable Algorithms for Learning and Variational Inference in Undirected Graphical Models
… complex distributions in a way which facilitates probabilistic reasoning, with numerous applications across machine learning and the sciences. This thesis deals with algorithmic and statistical problems of learning a high-dimensional graphical model from samples, and related problems of performing …
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A multiple secretary problem with switch costs
In this thesis, we utilize probabilistic reasoning and simulation methods to determine the optimal selection rule for the secretary problem with switch costs, in which a known number of applicants appear sequentially in a random order, and the objective is to maximize the sum of the qualities of …
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An Approach for Fast Score Computation in Bayesian Network Structure Learning Over Large-Scale Distributed Data
… of an event. In consequence, its suitability for probabilistic reasoning 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). …
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Natively probabilistic computation
I introduce a new set of natively probabilistic computing abstractions, including probabilistic generalizations of Boolean circuits, backtracking search and pure Lisp. I show how these tools let one compactly specify probabilistic generative models, generalize and parallelize widely used sampling …
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Automated Vocabulary Building for Characterizing and Forecasting Elections using Social Media Analytics
… algorithm that builds a dynamic vocabulary using Probabilistic Soft Logic (PSL), a framework for probabilistic reasoning over relational domains. Using eight presidential elections from Latin America, we show how our query expansion methodology improves the performance of traditional election …
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Lifted First-Order Probabilistic Inference
… division in AI between logical symbolic and probabilistic reasoning approaches. While probabilistic models can deal well with inherent uncertainty in many real-world domains, they operate on a mostly propositional level. Logic systems, on the other hand, can deal with much richer …
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A probabilistic architecture for algorithm portfolios
Heuristic algorithms for logical reasoning are increasingly successful on computationally difficult problems such as satisfiability, and these solvers enable applications from circuit verification to software synthesis. Whether a problem instance can be solved, however, often depends in practice on …
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The Development of Introductory Statistics Students' Informal Inferential Reasoning and Its Relationship to Formal Inferential Reasoning
… been studied as a means to introduce inferential reasoning well before and without the formalities of formal statistical inference. This mixed methods study investigated the development of introductory statistics students' informal inferential reasoning and its relationship to their formal …
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