Physical Sciences and Mathematics Commons^™

Self-Supervised Representation Learning For Motion Time Series: A Case Study In Activity Recognition, Luis Carlos Garza Perez

Theses and Dissertations

In this thesis we will learn about what contrastive learning and time series are and understand the differences between supervised and self-supervised frameworks in machine learning. In addition, we will describe how the newest and most efficient self-supervised learning framework for visual representations to this date works, called SimCLR, which was originally developed to obtain useful vector representations from static images. We will also explain what TS2Vec is, and how a combination of both approaches can be applied to the concept of a time series, and still be able to extract a vector representation of the subject described by the …

Atomlbs: An Atom Based Convolutional Neural Network For Druggable Ligand Binding Site Prediction, Md Ashraful Islam

Theses and Dissertations

Despite advances in drug research and development, there are few and ineffective treatments for a variety of diseases. Virtual screening can drastically reduce costs and accelerate the drug discovery process. Binding site identification is one of the initial and most important steps in structure-based virtual screening. Identifying and defining protein cavities that are likely to bind to a small compound is the objective of this task. In this research, we propose four different convolutional neural networks for predicting ligand-binding sites in proteins. A parallel optimized data pipeline is created to enable faster training of these neural network models on minimal …

Hardware Isolation Approach To Securely Use Untrusted Gpus In Cloud Environments For Machine Learning, Lucas D. Hall

Theses and Dissertations

Machine Learning (ML) is now a primary method for getting useful information out of the immense volumes of data being generated and stored in society today. Useful data is a commodity for training ML models and those that need data for training are often not the owners of the data leading to a desire to use cloud-based services. Deep learning algorithms are best suited to run on a graphical processing unit (GPU) which presents a specific problem since the GPU is not a secure or trusted piece of hardware in the cloud computing environment.

In this paper, we will analyze …

Factors Influencing Intent To Take A Covid-19 Test In The United States, Sheila Rutto

Theses and Dissertations

In 2020, COVID-19 became the first pandemic in the world’s history that brought the entire world to an abrupt and unexpected halt. Since the first reported case of the disease to date, the novel coronavirus has been able to wreak havoc in literary every corner of the globe and left an ever-growing number of unprecedented fatalities. The normal way of life has been disrupted, and the level of uncertainty about the end of this pandemic continues to manifest to many. Due to the urgency to bring this pandemic under control, medical officers have been able to recommend actions that people …

A Targeted Adversarial Attack On Support Vector Machine Using The Boundary Line, Yessenia Rodriguez

Theses and Dissertations

In this thesis, a targeted adversarial attack is explored on a Support Vector Machine (SVM). SVM is defined by creating a separating boundary between two classes. Using a target class, any input can be modified to cross the “boundary line,” making the model predict the target class. To limit the modification, a percentage of an image of the target class is used to get several random sections. Using these sections, the input will be moved in small steps closer to the boundary point. The section that took the least number of steps to cause the model to predict the target …

Comparison Of Rl Algorithms For Learning To Learn Problems, Adolfo Gonzalez Iii

Theses and Dissertations

Machine learning has been applied to many different problems successfully due to the expressiveness of neural networks and simplicity of first order optimization algorithms. The latter being a vital piece needed for training large neural networks efficiently. Many of these algorithms were produced with behavior produced by experiments and intuition. An interesting question that comes to mind is that rather than observing and then designing algorithms with beneficial behaviors, can these algorithms be learned through a reinforcement learning by modeling optimization as a game. This paper explores several reinforcement learning algorithms which are applied to learn policies suited for optimization.

Using Machine Learning To Predict Student Achievement On The State Of Texas Assessment Of Academic Readiness Examination In Charter Schools, Christopher D. Gonzalez

Theses and Dissertations

The purpose of this study was to research and develop a way to use machine learning algorithms (MLAs) to predict student achievement on the State of Texas Assessment of Academic Readiness (STAAR), specifically in the charter school setting. Charter schools have the disadvantage of a constant influx in students, so providing historical student data in order to analyze trends proves difficult. This study expands on previous research done on students in secondary and post-secondary school and determining features that indicate success in these settings. The data used is from the district of IDEA Public Schools who focuses on providing education …

A Comparative Approach To Question Answering Systems, Josue Balandrano Coronel

Theses and Dissertations

In this paper I will analyze three different algorithms and approaches to implement Question Answering Systems (QA-Systems). I will analyze the efficiency, strengths, and weaknesses of multiple algorithms by explaining them in detail and comparing them with each other. The overarching aim of this thesis is to explore ideas that can be used to create a truly open context QA-System. Open context QA-Systems remain an open problem.

The various algorithms and approaches presented in this work will be focused on complex questions. Complex questions are usually verbose and the context of the question is equally important to answer the query …