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Skip to Search Results- 54Artificial Intelligence
- 31Machine Learning
- 30Natural Language Processing
- 13Reinforcement Learning
- 10Deep Learning
- 5Computer Vision
- 1Akbari, Mojtaba
- 1Alexander, Graham
- 1Asadi Atui, Kavosh
- 1Ashley, Dylan R
- 1Ashrafi Asli, Seyed Arad
- 1Atrazhev, Peter
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Application of Natural Language Processing and Information Retrieval in Two Software Engineering Tools
DownloadFall 2021
Many software engineering problems have traditionally been approached by applying techniques based on static analysis and fixed sets of rules. I created two novel techniques to tackle three software engineering problems: typo location, fix suggestion, and crash report bucket creation. However,...
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Spring 2022
The rapid increase in global water and energy demand due to industrialization and population growth is a pressing challenge humankind faces today. Recent estimates indicate that due to population growth and reduction of water supplies, 40% of the global population is struggling with water...
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An Empirical Study on Learning and Improving the Search Objective for Unsupervised Paraphrasing
DownloadSpring 2022
Research in unsupervised text generation has been gaining attention over the years. One recent approach is local search towards a heuristically defined objective, which specifies language fluency, semantic meanings, and other task-specific attributes. Search in the sentence space is realized by...
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Spring 2024
We introduce the background of the natural language processing field, outlining the benefits and drawbacks of rule-based versus statistical methods. We present knowledge graphs as a way to integrate the explainability of rule-based methods and the power of statistical methods, large language...
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Spring 2023
With machine learning models becoming more complicated and more widely applied to solve real-world challenges, there comes the need to explain their reasoning. In parallel with the advancements of deep learning methods, Explainable AI (XAI) algorithms have been proposed to address the issue of...
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Fall 2022
Graph-based Knowledge Bases (KBs) are composed of relational facts that can be perceived as two entities, called head and tail, linked through a relation. Processes of constructing KBs, i.e., populating them with such facts, as well as revising and updating them are of special importance. Such...
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Fall 2024
The success of deep learning is partly due to the sheer size of modern models. However, such large models strain the capabilities of mobile or resourceconstrained devices. Ergo, reducing the resource demands of AI models is essential before AI can be deployed on such devices. One promising...
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Automated Coordination of Distributed Energy Resources using Local Energy Markets and Reinforcement Learning
DownloadFall 2024
The conventional unidirectional model of the electricity grid operations is no longer sufficient. The continued proliferation of distributed energy resources and the resultant surge in net load variability at the grid edge necessitates deploying adequate demand response methods. This thesis...
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Spring 2021
It has gotten increasingly harder for laypersons to determine the veracity of online health information. This is because of the explosion of content in health social media, allowing anyone with an Internet connection to create and propagate health-related content. This includes both innocuous and...
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Spring 2021
Learning about many things can provide numerous benefits to a reinforcement learning system. For example, learning many auxiliary value functions, in addition to optimizing the environmental reward, appears to improve both exploration and representation learning. The question we tackle in this...