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 12 of 12 for “"dense matrices"”.
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Spectral Regression: A Regression Framework for Efficient Regularized Subspace Learning
… usually involve eigen-decomposition of dense matrices which is expensive in both time and memory. In this thesis, we introduce a novel dimensionality reduction framework, called {\bf Spectral Regression} (SR). SR casts the problem of learning an embedding function into a regression …
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Mobile array designs with ANSERLIN antennas and efficient, wide-band PEEC models for interconnect and power distribution network analysis
… the method of moments, the PEEC method generates dense matrices for its cell interactions. This thesis contains research focused on efficiently using a limited number of cells for accurate results. This has been approached with a hybrid method and also with grid refinements. Additionally, the …
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The stochastic operator approach to random matrix theory
Classical random matrix models are formed from dense matrices with Gaussian entries. Their eigenvalues have features that have been observed in combinatorics, statistical mechanics, quantum mechanics, and even the zeros of the Riemann zeta function. However, their eigenvectors are …
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Fast algorithm and surface integral equations for two-dimensional materials modeling
… transform (DFT), the multipole expansions with dense matrices can be transformed to diagonal matrices with stable accuracy. Therefore a broadband 2D FMA with high efficiency and accuracy is achieved with a multi-level scheme. Then a metasurface platform to generate structured light at second …
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Hypergraph-Based Combinatorial Optimization of Matrix-Vector Multiplication
… multiplication for relatively small, dense matrices that arise in finite element assembly. Previous work showed that combinatorial optimization of matrix-vector multiplication can lead to faster assembly of finite element stiffness matrices by eliminating redundant operations. Based on …
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Systems Pharmacology – Machine Learning Approaches in Profiling Oncology Drug Candidates
… descriptors. We generated both sparse and dense matrices for modeling. We cross-validated, parameter hypertuned, and evaluated model performance on different statistical performance metrics, including Receiver-Operating Characteristic (ROC) curves. We investigated the full and reduced model …
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Algorithms and technologies for photonic crystal modelling
… meshless method requires the creation of large dense matrices and then forms a generalised eigenvalue problem. A new set of algorithms were developed that can model photonic crystals accurately. Exploration of alternative technologies was carried out to try to obtain a speed up in the modelling …
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Coupling in SPDEs and spectral analysis of heavy-tailed random operators
… (random Schrödinger operators and random matrices). It is divided into three parts. In the first part, the author considers infinite dimensional stochastic PDEs defined on an abstract Hilbert space, and the main contribution is a solution theory for such SPDEs when the coefficient in front …
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Automatically Optimizing Tree Traversal Algorithms
… to regular applications, which operate over dense matrices and arrays, irregular programs manipulate and traverse complex data structures like trees and graphs. As irregular applications operate on ever larger datasets, their performance suffers from poor locality and parallelism. Programmers …
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The proxy point method for rank-structured matrices
… used to reduce computation and storage cost for dense matrices defined by interactions between many bodies. The main bottleneck for their application is the expensive computation required to represent a matrix in a rank-structured matrix format which involves compressing specific matrix blocks …
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Accelerating graph computation with system optimizations and algorithmic design
… formulation of the problem uses a series of dense matrix multiplies that are space inefficient, and the matrix formulation makes it difficult to use fine-grained graph techniques like sampling. We formulate the GTN problem as a graph problem that is more space efficient as it does not need …