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- 25Natural Language Processing
- 22Artificial Intelligence
- 18Reinforcement Learning
- 16Deep Learning
- 16Neural Networks
- 2Wen, Junfeng
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- 1Al Dallal, Ahmed
- 1Al-Masri, Mohammad
- 1Alam Anik, Md Tanvir
- 1Alateeq, Majed Mohammad
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Addressing the Challenges of Applying Machine Learning for Predicting Mental Disorders and Their Prognosis Using Two Case Studies
DownloadSpring 2019
Ghoreishiamiri, Seyedehreyhaneh
One of the principal applications of machine learning in psychiatry is to build automated tools that can help clinicians predict the diagnosis and prognosis of mental disorders using available data from patients’ profiles. Here, in two different studies, we investigate ways to use machine learn-...
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Spring 2023
Wheelchair-mounted robotic manipulators have the potential to help the elderly and individuals living with disabilities carry out their activities of daily living independently. While robotics researchers focus on assistive tasks from the perspective of various control schemes and motion types, ...
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Fall 2023
Skin moles are one of the most commonly occurring dermatological conditions prevalent nowadays. Early identification and diagnosis of moles are absolutely crucial since they often turn out to be precursors to serious conditions such as melanoma, a dangerous type of skin cancer. Therefore, to...
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An approach for Evaluating the Full Truck and Full Bucket Loading Strategies in Open-Pit Mining Using a Discrete Event Simulation and Machine Learning
DownloadFall 2022
Material loading and hauling are crucial factors in the mining industry, comprising over 50% of the costs. Many studies covered optimization and improving the efficiency of truck-shovel operations. Decreasing operating costs is vital for mining companies to remain profitable and feasible....
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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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An Exploration of Dialog Act Classification in Open-domain Conversational Agents and the Applicability of Text Data Augmentation
DownloadFall 2023
Recognizing dialog acts of users is an essential component in building successful conversational agents. In this work, we propose a dialog act (DA) classifier for two of our open domain conversational agents. For this, we curated a high-quality, multi-domain dataset with ∼24k user utterances...
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Spring 2020
The predictive representations hypothesis is that representing the state of the world in terms of predictions about the future will result in good generalization. In this thesis, good generalization is specifically quantified by good learning performance in both accuracy and speed when predicting...
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Fall 2023
Critical point calculations are a topic of great importance and a fundamental part of classical thermodynamics. While the basis of this field is hundreds of years old, the effective handling of complex, multicomponent fluid mixtures has been an ongoing area of study over the past 50 years. Two...
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Analysis of the effectiveness of magnetic filters of shovel hydraulic system and successive hydraulic failure prediction using data-driven approaches
DownloadFall 2022
Surface mining dominates the world's production of minerals. Currently, almost all non-metallic minerals (more than 95 %), most metallic minerals (more than 90%), and a significant fraction of coal (more than 60%) are mined by surface mining methods. The hydraulic shovel-truck system forms the...
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Spring 2021
Deep learning has revolutionized many fields that process large amounts of data such as images, video, audio, speech, and text. Anomaly detection, however, is among the areas that still require major advancements. Based on the key traits of deep learning, which are the need for very little hand...