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 20 of 39 for “"Machine Learning System"”.
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Feature Factory : a collaborative, crowd-sourced machine learning system
… thesis, I designed, implemented, and tested a machine learning learning system designed to crowd-source feature discovery called Feature Factory. Feature Factory provides a complete web-based platform for users to define, extract, and test features on any given machine learning problem. This …
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Toward efficient online scheduling for large-scale distributed machine learning system
<p>Thanks to the rise of machine learning (ML) and its vast applications, recent years have witnessed a rapid growth of large-scale distributed ML frameworks, which exploit the massive parallelism of computing clusters to expedite ML training jobs. However, the proliferation of large-scale …
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A Systems Theory Approach to Cybersecuring a Supervised Machine Learning System
Machine learning is a rapidly growing field with many applications in areas such as healthcare, finance, and transportation. As machine learning becomes more prevalent, it is important to ensure that these systems are secure and can resist attacks from malicious actors. This is particularly …
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PreCog : a robust machine learning system to predict failure in a virtualized environment
… in this work addresses the need for a warning system to predict future application failures. PreCog, the predictive and regressional error correlating guide system, aims to aid administrators by providing a robust future failure warning system statistically induced from past system behavior. In …
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Element Detection in Japanese Comic Book Panels
… possible today. Our approach uses an expert system and a machine learning system. The expert system process information from images and inspires feature sets which help train the machine learning system. The expert system detects speech bubbles based on heuristics. The machine learning system …
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Assessment of Individual Differences in Online Social Networks Using Machine Learning
… behaviour, and I investigate if an automated machine learning system can measure the same psychological factors, only from observing the footprints of online behaviour, without observing any offline behaviour or any direct input from the individual. Prior research shows that psychological …
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Towards understanding and simplifying human-in-the-loop machine learning
"Machine learning application developers and data scientists spend inordinate amount of time iterating on machine learning (ML) workflows, by modifying the data pre-processing, model training, and post-processing steps, via trial-and-error to achieve the desired model performance. As a result, …
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Adaptive Preference Learning With Bandit Feedback: Information Filtering, Dueling Bandits and Incentivizing Exploration
In this thesis, we study adaptive preference learning, in which a machine learning system learns users' preferences from feedback while simultaneously using these learned preferences to help them find preferred items. We study three different types of user feedback in three application setting: …
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Image Miner : an architecture to support deep mining of images
In this thesis, I designed a cloud based system, called ImageMiner, to tune parameters of feature extraction process in a machine learning pipeline for images. Feature extraction is a key component of the machine learning pipeline, and tune its parameters to extract the best features can have …
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Lexical Aspectual Classification
… These seeds are in turn fed into a supervised machine learning system, trained on 136 lexical and syntactic features. I experiment on one 8-way classification task, one 3-way classification task, and ten binary classification tasks, and show that five of the eight classes are identified better …
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GENERIC: Musical Improvisation with Machine Learning and Generative Composition
… existing musical works involving humans and AI systems, beginning near the advent of the digital computer and progressing through contemporary works. The project culminated in the creation of an eponymous musical suite for clarinet and electronics, in which a musical work was composed …
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Using distributed machine learning to predict arterial blood pressure
This thesis describes how to build a flow for machine learning on large volumes of data. The end result is EC-Flow, an end to end tool for using the EC-Star distributed machine learning system. The current problem is that analysing datasets on the order of hundreds of gigabytes requires overcoming …
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FlexGP 2.0 : multiple levels of parallelism in distributed machine learning via genetic programming
… presents FlexGP 2.0, a distributed cloud-backed machine learning system. FlexGP 2.0 features multiple levels of parallelism which provide a significant improvement in accuracy v.s. elapsed time. The amount of computational resources in FlexGP 2.0 can be scaled along several dimensions to support …
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LIDS: An Extended LSTM Based Web Intrusion Detection System With Active and Distributed Learning
Intrusion detection systems are an integral part of web application security. As Internet use continues to increase, the demand for fast, accurate intrusion detection systems has grown. Various IDSs like Snort, Zeek, Solarwinds SEM, and Sleuth9, detect malicious intent based on existing patterns of …
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Accelerating human-in-the-loop machine learning
Machine learning workflow development is a process of trial-and-error: developers iterate on workflows by testing out small modifications until the desired accuracy is achieved. Unfortunately, existing machine learning systems focus narrowly on model training—a small fraction of the overall …
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Machine learning blocks
This work presents MLBlocks, a machine learning system that lets data scientists explore the space of modeling techniques in a very easy and efficient manner. We show how the system is very general in the sense that virtually any problem and dataset can be casted to use MLBlocks, and how it …
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Deep learning for Alzheimer’s disease: towards the development of an assistive diagnostic tool
… witnessed rapid advances at the intersection of machine learning and medicine. Owing to the tremendous amount of digitized hospital data, machine learning is poised to bring innovation to the traditional healthcare workflow. Though machine learning models have strong predictive power, it is …
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Machine Learning for Reconstructing Dynamic Protein Structures from Cryo-EM Images
… other biomolecules form dynamic macromolecular machines that carry out essential biological processes responsible for life. However, studying the mechanisms of these biomolecular complexes at relevant atomic-scale resolutions is an extraordinarily challenging task in structural biology. This …
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Enhancement of network security by use machine learning
… simulation on enhancement network security using machine learning. The design use MATLAB coding to show the simulation. The coding is designed in a way that there is an attack of malicious to destroy the data. Because there is a machine-learning scheme in the security, the system have done …
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Gaze Estimation with Graphics
Gaze estimation systems determine where someone is looking. Gaze is used for a wide range of applications including market research, usability studies, and gaze-based interfaces. Traditional equipment uses special hardware. To bring gaze estimation mainstream, researchers are exploring approaches …
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