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Full-Text Articles in Physical Sciences and Mathematics
Numerical Decoding, Johnson-Lindenstrauss Transforms, And Linear Codes, Yue Mao
Numerical Decoding, Johnson-Lindenstrauss Transforms, And Linear Codes, Yue Mao
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Many computational problems are related to the model y = Ax + e, including compressive sensing, coding theory, dimensionality reduction, etc. The related algorithms are extremely useful in practical applications for high performance computing, for example, digital communications, biological imaging and data streaming, etc. This thesis studies two important problems. One problem is related to efficient decoding for Reed-Solomon codes over complex numbers. In this case, A and y are given, and the goal is to find an efficient stable algorithm to compute x. This is related to magnetic resonance imaging (MRI). The other problem is related to fast algorithms …
Homomorphic Encryption And The Approximate Gcd Problem, Nathanael Black
Homomorphic Encryption And The Approximate Gcd Problem, Nathanael Black
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With the advent of cloud computing, everyone from Fortune 500 businesses to personal consumers to the US government is storing massive amounts of sensitive data in service centers that may not be trustworthy. It is of vital importance to leverage the benefits of storing data in the cloud while simultaneously ensuring the privacy of the data. Homomorphic encryption allows one to securely delegate the processing of private data. As such, it has managed to hit the sweet spot of academic interest and industry demand. Though the concept was proposed in the 1970s, no cryptosystem realizing this goal existed until Craig …
Grobner Bases: Degree Bounds And Generic Ideals, Juliane Golubinski Capaverde
Grobner Bases: Degree Bounds And Generic Ideals, Juliane Golubinski Capaverde
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In this thesis, we study two problems related to Gröbner basis theory: degree bounds for general ideals and Gröbner bases structure for generic ideals. We start by giving an introduction to Gröbner bases and their basic properties and presenting a recent algorithm by Gao, Volny and Wang. Next, we survey degree bounds for the ideal membership problem, the effective Nullstellensatz, and polynomials in minimal Gröbner bases. We present general upper bounds, and bounds for several classes of special ideals. We provide classical examples showing some of these bounds cannot be improved in general. We present a comprehensive study of a …
Applied Statistics In Environmental Monitoring: Case Studies And Analysis For The Michigan Bald Eagle Biosentinel Program, Katherine Leith
Applied Statistics In Environmental Monitoring: Case Studies And Analysis For The Michigan Bald Eagle Biosentinel Program, Katherine Leith
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The bald eagle (Haliaeetus leucocephalus) is an extensively researched tertiary predator. Its life history and the impact of various stressors on its reproductive outcomes have been documented in many studies, and over many years. Furthermore, the bald eagle population recovery in Michigan has been closely monitored since the 1960s, as it has continued to recover from a contaminant-induced bottleneck. Because of its position at the top of the aquatic food web and the large body of ethological knowledge, the bald eagle has become a sentinel species for the Michigan aquatic ecosystem. In April 1999, the Michigan Department of Environmental Qualtity, …
On Numerical Algorithms For Fluid Flow Regularization Models, Abigail Bowers
On Numerical Algorithms For Fluid Flow Regularization Models, Abigail Bowers
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This thesis studies regularization models as a way to approximate a flow simulation at a lower computational cost. The Leray model is more easily computed than the Navier-Stokes equations (NSE), and it is more computationally attractive than the NS-α regularization because it admits a natural linearization which decouples the mass/momentum system and the filter system, allowing for efficient and stable computations. A major disadvantage of the Leray model lies in its inaccuracy. Thus, we study herein several methods to improve the accuracy of the model, while still retaining many of its attractive properties. This thesis is arranged as follows. Chapter …
Level Stripping Of Genus 2 Siegel Modular Forms, Rodney Keaton
Level Stripping Of Genus 2 Siegel Modular Forms, Rodney Keaton
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In this Dissertation we consider stripping primes from the level of genus 2 cuspidal Siegel eigenforms. Specifically, given an eigenform of level Nlr which satisfies certain mild conditions, where l is a prime not dividing N, we construct an eigenform of level N which is congruent to our original form. To obtain our results, we use explicit constructions of Eisenstein series and theta functions to adapt ideas from a level stripping result on elliptic modular forms. Furthermore, we give applications of this result to Galois representations and provide evidence for an analog of Serre's conjecture in the genus 2 case.
Convergence Of A Reinforcement Learning Algorithm In Continuous Domains, Stephen Carden
Convergence Of A Reinforcement Learning Algorithm In Continuous Domains, Stephen Carden
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In the field of Reinforcement Learning, Markov Decision Processes with a finite number of states and actions have been well studied, and there exist algorithms capable of producing a sequence of policies which converge to an optimal policy with probability one. Convergence guarantees for problems with continuous states also exist. Until recently, no online algorithm for continuous states and continuous actions has been proven to produce optimal policies. This Dissertation contains the results of research into reinforcement learning algorithms for problems in which both the state and action spaces are continuous. The problems to be solved are introduced formally as …