Browsing UMBC Mathematics and Statistics Department by Title
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Adaptively Solving the LocalMinimum Problem for Deep Neural Networks
This paper aims to overcome a fundamental problem in the theory and application of deep neural networks (DNNs). We propose a method to solve the local minimum problem in training DNNs directly. Our method is based on the ... 
Analyzing TwoDimensional Gel Images
(Taylor and Francis Online, 20120920) 
Application of adaptive ANOVA and reduced basis methods to the stochastic StokesBrinkman problem
(20210213)The StokesBrinkman equations model fluid flow in highly heterogeneous porous media. In this paper, we consider the numerical solution of the StokesBrinkman equations with stochastic permeabilities, where the permeabilities ... 
Applications of Tensor Decompositions
(2016)This report explores how data structures known as tensors can be used to perform multidimensional data analysis. If a matrix can be thought of as a twodimensional array, then a tensor can be thought of as a multidimensional ... 
An Approach to Tuning Hyperparameters in Parallel: A Performance Study Using Climate Data CyberTraining: Big Data + HighPerformance Computing + Atmospheric Sciences
(2019)The ability to predict violent storms and bad weather conditions with current models can be difficult due to the immense complexity associated with weather simulation. For example when predicting a tornado caution must be ... 
An Approximate Fisher Scoring Algorithm for Finite Mixtures of Multinomials
Finite mixture distributions arise naturally in many applications including clustering and classi cation. Since they usually do not yield closed forms for maximum likelihood estimates (MLEs), numerical methods using the ... 
Assessing Climate Impacts on Regional Water Resources in the Midwestern US
(2015)It is well documented that decadal climate variability (DCV) has a signi cant impact on water resources in the Missouri River Basin (MRB). This project aims to utilize multidecadal simulations of Global Climate Models ... 
Assessing Water Budget Sensitivity to Precipitation Forcing Errors in Potomac River Basin Using the VIC Hydrologic Model CyberTraining: Big Data + HighPerformance Computing + Atmospheric Sciences
(2019)The Potomac River Basin is a watershed located on the East Coast of the USA across West Virginia, Virginia, Pennsylvania, Maryland, and the District of Columbia. Interannual variations in precipitation makes it challenging ... 
Assessment of Simple and Alternative Bayesian Ranking Methods Utilizing Parallel Computing
(2011)The U.S. Census Bureau (USCB) assists the federal government in distributing approximately $400 billion of aid by providing a complete ranking of the states according to certain criteria, such as average poverty level. It ... 
Attractors and Determining Functionals for A Flutter Model: Finite Dimensionality Out of Thin Air
(20190424)We establish the effective {\em finite dimensionality} of the dynamics corresponding to a flowplate interaction PDE model arising in aeroelasticity: a nonlinear panel, in the absence of rotational inertia, immersed in an ... 
A parallel simulation of the evolution of transcription factor binding sites
(20110527)The analysis of transcription factor binding motifs may aid in understanding the process by which transcription factors recognize their binding sites. We wish to investigate the likelihood that transcription factors use ... 
Benchmarking parallel implementations of cloud type clustering from satellite data
The study of clouds, i.e., where they occur and what are their characteristics, plays a key role in the understanding of climate change. The aim of this project is to use machine learning in conjunction with parallel ... 
Benchmarking Parallel KMeans Cloud Type Clustering from Satellite Data
(Springer, Cham, 20191008)The study of clouds, i.e., where they occur and what are their characteristics, plays a key role in the understanding of climate change. Clustering is a common machine learning technique used in atmospheric science to ... 
Block Cyclic Distribution of Data in pbdR and its Effects on Computational Efficiency
(2013)Programming with big data in R (pbdR), a package used to implement highperformance computing in the statistical software R, uses block cyclic distribution to organize large data across many processes. Because computations ... 
Calcium Induced Calcium Release with Stochastic Uniform Flux Density in a Heart Cell
(Society for Computer Simulation International (SCS), 20150726)Calcium is a critical component in many cellular functions. It serves many important functions such as signal transduction, contraction of muscles, enzyme function, and maintaining potential difference across excitable ... 
CAREERRELEVANT MATHEMATICS PATHWAYS: ON THE ROAD TO STUDENT SUCCESS
UMBC, a diverse public research university, has a reputation for producing highly capable undergraduate scholars. Unfortunately, many students place into mathematics courses at a lower level than those that offer degree ... 
A Chromatic Dispersion Estimation Method for Arbitrary Modulation Formats
(Optical Society of America, 20110506)Simulations show that a modulationformatindependent method for estimating chromatic dispersion from the phase of a coherentlyreceived signal at four frequencies can estimate 3000 ps/nm of dispersion to within 2% at an ... 
Cluster Computing using Intel Concurrent Collections
(2012)The Intel Corporation is developing a new parallel software and compiler called Concurrent Collections (CnC) to make programming in parallel easier for the user. CnC provides a system of collections comprised of steps, ... 
Clustering of Multidimensional Data Sets with Applications to Spatial Distributions of Ribosomal Proteins
(2013)Consider ribosomal proteins, each with a threedimensional spatial location. Proteins related to the cofactor phenotype may be randomly or nonrandomly distributed within the ribosome. To investigate this question, the ... 
Commutation principles for optimization problems on spectral sets in Euclidean Jordan algebras
(20200910)The commutation principle of Ramirez, Seeger, and Sossa proved in the setting of Euclidean Jordan algebras says that when the sum of a real valued function h and a spectral function Φ is minimized/maximized over a spectral ...