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 1040 for “"dimensionality"”.
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Geometric Dimensionality Reduction
… has resulted in a surge of research into dimensionality reduction techniques that spans across numerous mathematical disciplines. In this thesis we establish Geometric Dimensionality Reduction, a non-linear data compression technique that utilizes low dimensional manifolds embedded in …
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Exploring the dimensionality of speech using manifold learning and dimensionality reduction methods
… subset of all producible sounds. A number of dimensionality reduction methods capable of discovering such underlying structure have previously been applied to speech. However, if speech lies on a manifold nonlinearly embedded in high-dimensional space, as has been proposed in the past, classic …
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Federated Linear Dimensionality Reduction
… Concretely, we focus primarily on linear dimensionality reduction and, in particular, on Principal Component Analysis (PCA) due to its pervasiveness, along with its ability to process unstructured data. The first advancement we introduce is a novel algorithm to perform streaming and …
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On Dimensionality Reduction of Data
… method is one of the important tools for the dimensionality reduction of data which can be made efficient with strong error guarantees. In this thesis, we focus on linear transforms of high dimensional data to the low dimensional space satisfying the Johnson-Lindenstrauss lemma. In addition, …
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Two dimensionality in magnetic interpretation
Thesis (M.S.)--Michigan State University. Dept. of Geology, 1970
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The Dimensionality of Educational Beliefs
From numerous polls, surveys, and personal experience of school administrators, it is clear that lay citizens hold a variety of beliefs about education. It is not clear, however, to what extent these beliefs are organized along the lines of several more embracing ideologies or movements in …
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Statistical models with diverging dimensionality
… analysis for one-way ANOVA with diverging dimensionality and iii) statistical analysis for multi-task learning.
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Enhancing dimensionality in remote sensing images
… and spectral resolutions. This variation in dimensionality presents challenges for image processing and analysis, necessitating techniques to enhance spatial, spectral, or combined spatial spectral resolutions. Dimensionality enhancement in remote sensing focuses on three primary tasks. …
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Autoencoder-based image dimensionality reduction methods
In this thesis, we study how images can be represented in a more compact way that still captures their most important features and preserves the similarities and dissimilarities between the images. These compact representations of images, also known as ‘image encodings’, allow us to identify …
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Graph Embedding and Nonlinear Dimensionality Reduction
… have been applied to many graph embedding and dimensionality reduction tasks. These methods aim to find low-dimensional representations of data that preserve its inherent structure. However, these methods often perform poorly when applied to data which does not lie exactly near a linear …
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Children's friendship choice and classroom dimensionality
… classification. Then, the effects of classroom dimensionality differences were investigated in relation to children's perceptions of their peers' ""smartness,"" troublesomeness, self-image related to school, and estimated teacher's expectation. Also, the relationships between these indices and …
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Dimensionality reduction for k-means clustering
In this thesis we study dimensionality reduction techniques for approximate k-means clustering. Given a large dataset, we consider how to quickly compress to a smaller dataset (a sketch), such that solving the k-means clustering problem on the sketch will give an approximately optimal solution on …
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Magnetic ordering in systems of reduced dimensionality
The magnetic behaviour of thin films of (111) FCC structures and (0001) corundum structured materials were studied by the mean field analysis and some Monte Carlo simulation. These models were conditioned on a mapping from first principles calculations to the Ising model. The effect of the …
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Sexual harassment proclivity : dimensionality and individual differences
Sexual harassment proclivity is an important but understudied domain of human conduct. The most widely used measure solely assesses the use of professional power to obtain sexual favors from subordinates. This single dimension does not reflect the full scope of behaviors that are subsumed under the …
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On Sequence Clustering and Supervised Dimensionality Reduction
… identically generated random sequences, and 2) dimensionality reduction for classification problems. </p> <p>For sequence clustering, the focus is on large sample performance of classical clustering algorithms, including the k-medoids algorithm and hierarchical agglomerative clustering (HAC) …
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Assessing The Dimensionality of Polytomous Item Exams
<p> Unidimensionality is a main assumption for Item Response Theory (IRT) models that are applied to statewide standardized tests for purposes such as scoring, equating, scaling, and DIF analyses. Thus, it is important that the unidimensionality evaluation of tests be efficiently and effectively …
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Semi supervised weighted maximum variance dimensionality reduction
… in some scenarios. In those scenarios, the dimensionality reduction methods play a major role for extracting useful features. The two parameter weighted maximum variance (2P-WMV) is a generalized dimensionality reduction method of which principal component analysis (PCA) and maximum margin …
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Dimensionality reduction for sparse and structured matrices
Dimensionality reduction has become a critical tool for quickly solving massive matrix problems. Especially in modern data analysis and machine learning applications, an overabundance of data features or examples can make it impossible to apply standard algorithms efficiently. To address this …
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