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.
Results
Showing 1 to 11 of 11 for “"structural learning"”.
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Algorithms for structural learning with decompositions
… and complex interdependencies and constraints. Learning over expressive structures (called structural learning) is usually time-consuming as exploring the structured space can be an intractable problem. The goal of this thesis is to present different techniques for structural learning, which …
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Probabilistic SEM : an augmentation to classical Structural equation modelling
Structural equation modelling (SEM) is carried out with the aim of testing hypotheses on the model of the researcher in a quantitative way, using the sampled data. Although SEM has developed in many aspects over the past few decades, there are still numerous advances which can make SEM an even more …
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Relational memory processes in adults with autism spectrum disorder
… executive functions, and attention on memory, learning, and spatial navigation in ASD. In addition to memory behaviour, eye movements were measured. It was found that the EM impairment in ASD adults with average intellectual abilities persisted across a range of materials and types of …
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Interactive Online System for Mathematical Induction
… to teach mathematical induction with the help of structural learning, guided examples to build a strong base and real-time feedback of user inputs. Using Java Servlets, the system offers an interactive learning experience that mirrors traditional textbook notation while eliminating the obstacles …
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An enhanced Bayesian Network prediction model for football matches based on player performance
… to other classical statistical and machine learning approaches. However, existing prediction models rely solely on historical team features including the match statistical data as well as team statistical data, together with the historical features of team achievement such as ranking in …
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Causal structure of networks of stochastic processes
… any causal LDGs can be reconstructed through learning the corresponding DIGs. Another contribution is to propose an approach for learning causal interaction network of mutually exciting linear Hawkes processes. In such processes, a natural notion of functional causality exists between …
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Knowledge-fused Identification of Condition-specific Rewiring of Dependencies in Biological Networks
… of biological prior knowledge into network learning algorithms can effectively leverage domain knowledge, biological prior knowledge is neither condition-specific nor error-free, only serving as an aggregated source of partially-validated evidence under diverse experimental conditions. …
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Risk management system to guide building construction projects’ in developing countries: a case study of Nigeria
… Belief Network (BBN) model was developed by structural learning and used to examine the cause and effect relationship amongst the 27 critical risk factors. The developed BBN model was subjected to validation using a multiple case study of two building construction projects in Nigeria. The …
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Structured prediction with indirect supervision
… tasks can be exploited to simplify both the learning task and the annotation effort --- it is sometimes possible to supply partial and indirect supervision to only some of the target variables or to other variables that are derivatives of the target variables and thus reduce the supervision …
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Ensemble Tree-Based Machine Learning for Imaging Data
… comprehensive care. Although numerous machine learning algorithms, especially those used for imaging data, have been developed, dealing with unique structures in imaging data remained a big challenge. In this dissertation, we are proposing novel statistical tree-based methods with more …