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 20 of 165 for “"Statistical learning"”.
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Distributed Supervised Statistical Learning
… in practice. In the age of big data, distributed learning has gained popularity as a method to manage enormous datasets. In this thesis, we focus on distributed supervised statistical learning where sparse linear regression analysis is performed in a distributed framework. These methods are …
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Statistical learning with differential privacy
… methodologies for modern statistics and machine learning, integrating the robust guarantees offered by differential privacy. Differential privacy tools mostly operate by introducing carefully calibrated randomness into the training process, thereby ensuring privacy protections. However, this …
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Statistical learning in network architecture
… commercial relationships. This thesis espouses learning to embrace the Internet's inherent complexity, address diverse problems and provide a component of the network's continued evolution. Malicious nodes, cooperative competition and lack of instrumentation on the Internet imply an environment …
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Data Analytics for Statistical Learning
… format, the pre-processed data is analyzed using statistical tools. In this stage, called statistical learning of the data, analysts have two main objectives (1) develop a statistical model that captures the behavior of the process from a sample of the data (2) identify anomalies in the process. …
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The Statistical Learning Of Musical Expectancy
This project investigated the statistical learning of musical expectancy. As a secondary goal, the effects of the perceptual properties of tone set familiarity (Western vs. Bohlen-Pierce) and textural complexity (melody vs. harmony) on the robustness of that learning process were assessed. A series …
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STATISTICAL LEARNING FOR STANDARD MODEL PHENOMENOLOGY
… with a particular emphasis on modern machine learning tools used within the NNPDF approach. We first present NNPDF4.0, currently the most recent and most precise set of PDFs based on a global dataset. We then provide suggestions for improvements to the machine learning tools used for the …
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Statistical Learning Approaches to Information Filtering
… technologies. Novel and principled machine learning methods are proposed to model users' information needs. The work demonstrates that the uncertainty of user profiles and the connections between them can be effectively modelled by using probability theory and Bayes rule. As one major …
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Physics-Based Statistical Learning in Thermoacoustics
… system under investigation. To do this, we use statistical learning techniques in combination with an experimental dataset consisting of O(10^6) datapoints. The dataset is obtained from more than 210 hours of automated experiments on an electrically-heated vertical Rijke tube. We use the …
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Statistical learning for cyber physical system
… of cyber-physical systems in transportation. Statistical learning techniques offer a powerful approach to analyzing complex transportation data, providing insights that enhance safety measures and operational efficiencies. This dissertation underscores the pivotal role of statistical learning …
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Statistical Learning for Sequential Unstructured Data
… process, which often limits their scalable learning abilities. The emergence of neural network tools has enabled scalable learning for high-dimensional sequential data. From an algorithmic perspective, efforts are directed towards reducing dimensionality and representing unstructured data …
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Speling "Successful" Sucesfuly: Statistical Learning in Spelling
… in ‹trellis›. In Study 1, we tabulated statistical patterns with regards to doubling in English. In Study 2, we collected behavioral data to see if people were sensitive to these statistical patterns in doubling and to explore other factors that might influence doubling such as context, …
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Advanced Statistical Learning Methods in Image Processing
… three projects, in which we develop advanced statistical methods to address daunting challenges in three key imaging processing problems. First, in the image compression problem, we develop a scalable and model-based method called Compression through Adaptive Recursive Partitioning (CARP) to …
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Constraints on phonological statistical learning in adults
Auditory statistical learning studies typically explore whether participants can compute a given statistical pattern from an artificial language (e.g., classic transitional probability studies). Even when studies include several statistical cues, these cues often coincide (e.g., exploring how …
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Text-Independent Speaker Identification using Statistical Learning
… probability of error in the systems. Therefore, statistical learning methods or techniques are utilized in this thesis because they have proven to have high accuracy and efficiency in various other applications. The statistical methods used are Gaussian Mixture Models and Support Vector Machines. …
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Methods for convex optimization and statistical learning
… methods for convex optimization and problems in statistical machine learning. In the first part of this thesis, we present new results for the Frank-Wolfe method, with a particular focus on: (i) novel computational guarantees that apply for any step-size sequence, (ii) a novel adjustment to the …
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Structural and functional brain plasticity for statistical learning
… from navigating in a new environment to learning a language. These skills rely on our ability to extract spatial and temporal regularities, often with minimal explicit feedback, that is known as statistical learning. Despite the importance of statistical learning for making perceptual …
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Application of statistical learning theory to plankton image analysis
… This thesis addresses the problem by applying statistical machine learning to video images collected by an optical sampler, the Video Plankton Recorder (VPR). The research is focused on development of a real-time automatic plankton recognition system to estimate plankton abundance. The system …
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