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Construction Of Quot-Schemes, Majid Dehghani Jan 2024

Construction Of Quot-Schemes, Majid Dehghani

Electronic Theses and Dissertations

The Quot Scheme is a construction representing parameter spaces for quotient objects of sheaves or coherent modules over a scheme. It encapsulates families of quotients by fixing a certain quotient's structure. The Hilbert Scheme, a specific type of Quot Scheme, focuses on parameterizing subschemes of a fixed projective space by fixing their Hilbert polynomials. After recalling the basic concepts of the theory, we explain the Grothendieck’s Quot scheme construction and its Grassmannian embedding. Then we continue to an explicit construction of Quot scheme in the case of graded modules over graded rings.


On A Class Of James-Stein’S Estimators In High-Dimensional Data, Arash Aghaei Foroushani Jan 2024

On A Class Of James-Stein’S Estimators In High-Dimensional Data, Arash Aghaei Foroushani

Electronic Theses and Dissertations

In this thesis, we consider the estimation problem of the mean matrix of a multivariate normal distribution in high-dimensional data. Building upon the groundwork laid by Chételat and Wells (2012), we extend their method to the cases where the parameter is the mean matrix of a matrix normal distribution. In particular, we propose a novel class of James-Stein’s estimators for the mean matrix of a multivariate normal distribution with an unknown row covariance matrix and independent columns. Given a realistic assumption, we establish that our proposed estimator outperforms the classical maximum likelihood estimator (MLE) in the context of high-dimensional data. …


Rado Numbers For Two Systems Of Linear Equations, Anthony Glackin Jan 2024

Rado Numbers For Two Systems Of Linear Equations, Anthony Glackin

Electronic Theses and Dissertations

For any positive integer n and any equation E of either the form x1+x2+· · ·+xn = x0 or x1 + x2 + n = x0, the two-color Rado number R2(E) is the least integer such that any 2-coloring of the natural numbers 1 through R2(E) will contain a monochromatic solution to E. Let Ek be a system of k equations of the aforementioned form, where Ei represents the ith equation in Ek and the set I = {1, 2, . . . , k} is the set of indices of these equations. This thesis shows that the two-color Rado …


Contrastive Learning, With Application To Forensic Identification Of Source, Cole Ryan Patten Jan 2024

Contrastive Learning, With Application To Forensic Identification Of Source, Cole Ryan Patten

Electronic Theses and Dissertations

Forensic identification of source problems often fall under the category of verification problems, where recent advances in deep learning have been made by contrastive learning methods. Many forensic identification of source problems deal with a scarcity of data, an issue addressed by few-shot learning. In this work, we make specific what makes a neural network a contrastive network. We then consider the use of contrastive neural networks for few-shot learning classification problems and compare them to other statistical and deep learning methods. Our findings indicate similar performance between models trained by contrastive loss and models trained by cross-entropy loss. We …


Classification In Supervised Statistical Learning With The New Weighted Newton-Raphson Method, Toma Debnath Jan 2024

Classification In Supervised Statistical Learning With The New Weighted Newton-Raphson Method, Toma Debnath

Electronic Theses and Dissertations

In this thesis, the Weighted Newton-Raphson Method (WNRM), an innovative optimization technique, is introduced in statistical supervised learning for categorization and applied to a diabetes predictive model, to find maximum likelihood estimates. The iterative optimization method solves nonlinear systems of equations with singular Jacobian matrices and is a modification of the ordinary Newton-Raphson algorithm. The quadratic convergence of the WNRM, and high efficiency for optimizing nonlinear likelihood functions, whenever singularity in the Jacobians occur allow for an easy inclusion to classical categorization and generalized linear models such as the Logistic Regression model in supervised learning. The WNRM is thoroughly investigated …


Problems In Chemical Graph Theory Related To The Merrifield-Simmons And Hosoya Topological Indices, William B. O'Reilly Jan 2024

Problems In Chemical Graph Theory Related To The Merrifield-Simmons And Hosoya Topological Indices, William B. O'Reilly

Electronic Theses and Dissertations

In some sense, chemical graph theory applies graph theory to various physical sciences. This interdisciplinary field has significant applications to structure property relationships, as well as mathematical modeling. In particular, we focus on two important indices widely used in chemical graph theory, the Merrifield-Simmons index and Hosoya index. The Merrifield-Simmons index and the Hosoya index are two well-known topological indices used in mathematical chemistry for characterizing specific properties of chemical compounds. Substantial research has been done on the two indices in terms of enumerative problems and extremal questions. In this thesis, we survey known extremal results and consider the generalized …