Browsing Colleges and Schools by Author "Qian, Xiaoning"
Now showing items 21-40 of 89
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Yu, Xiaojing (2022-07-12)Generation is a fundamental sub-area in artificial intelligence. Compared with the remarkable progress in image generation, textual data generation still faces many challenges and is far from perfect. This dissertation ...
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Du, Mengnan (2021-12-07)Deep neural networks (DNNs) are progressing at an astounding rate, and these models have a wide range of real-world applications, such as movie recommendations of Netflix, neural machine translation of Google, speech ...
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Kim, Eunji (2019-10-08)The recent advancements in high-throughput technologies provide a wealth of information on gene expression patterns and gene-regulatory pathways. As a result, researchers in life sciences have an unprecedented opportunity ...
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Eresen, Aydin (2018-07-30)Golden retriever muscular dystrophy (GRMD) is a spontaneous X-linked canine model of Duchenne muscular dystrophy (DMD) with the affected animals developing a progressively fatal disease, similar to the human condition. As ...
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Wheat, Carter B (2022-12-08)Mosquitoes are able to breed and lay eggs in almost any area where there is stagnant water such as permanent bodies of water such as lakes and ponds and temporary small bodies of water caused by heavy rainfall, river or ...
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Kidd, Brian J. (2022-07-21)Directed graphs have widespread applicability, so there is continued need for both computational and theoretical improvements. We extend the standard methodology in three different ways, which constitute the main chapters ...
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Wan, Qing (2016-04-25)The foundation of Information theory by C. E. Shannon is the entropic measures to quantize the abstract concept of information in random variables. When the interest is to study the relationships among multiple random ...
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Jin, Qing (2018-11-06)Convolution neural networks have become one of the dominating deep learning models, especially for computation vision tasks such as image classification and segmentation. Dense convolution filters are inefficient, due to ...
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Reji, John Mathai (2020-07-30)Monte Carlo REINFORCE is used to design an algorithm to not only find the optimal deep learning architecture but also the optimal set of features that can maximize the performance of the said deep learning model. The ...
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He, Kai (2020-07-01)Longitudinal studies that employ repeated measures by following particular individuals over periods of time allow researchers to assess the development/changes in the characteristics of the target populations at both the ...
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Chen, Chun-Chi (2017-10-26)This dissertation studies the emerging topics in genome sequencing and analysis with DNA and RNA. The optimal hybrid sequencing and assembly for accurate genome reconstruction and efficient detection approaches for novel ...
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Kovuri, Pranoy (2019-07-12)Information extraction (IE) extracts meaningful knowledge from data. Two important tasks in IE are named entity recognition and relation extraction. Existing approaches in relation extraction treat entity and relation ...
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Liu, Yezi (2021-08-09)Knowledge graphs (KGs) have been widely applied as an efficient tool in storing information in the digital age. They always contain a considerable number of errors and could significantly affect downstream tasks. To tackle ...
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Lu, Jicheng (2020-11-17)Deep learning techniques produce impressive performance in many natural language processing tasks. However, it is still difficult to understand what the neural network learned during training and prediction. Recently, ...
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Aishwarya, Fnu (2018-04-25)Popular video sharing websites contain a large collection of videos in various sign languages. These websites have the potential of being a significant source of knowledge sharing and communication for the members of the ...
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Zhang, Ziyi (2021-04-19)The coronavirus (COVID-19) has caused a huge negative influence on the global. The virus continues to spread and has sickened more than 90,201,652 people until January 2021 and caused 1,937,091 deaths in the world. So far, ...
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Sui, Xiaopeng (2018-11-01)Unsupervised and semi-supervised learning are explored in convex clustering with metric learning while supervised learning is explored in a novel feature selection method. First, we evaluate the performance of convex ...
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Zhang, Lida (2023-05-15)With the development of biomedical sensing techniques and data storage, machine learning has been widely applied to many healthcare applications from the abundance of data resources. However, biomedical data, from real-world ...
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Zhang, Lida (2023-05-15)With the development of biomedical sensing techniques and data storage, machine learning has been widely applied to many healthcare applications from the abundance of data resources. However, biomedical data, from real-world ...
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Shao, Shuo (2017-04-28)Understanding the fundamental limits of communication systems involves both constructing efficient coding schemes as well as proving mathematically that certain performance is impossible to achieve; the latter is known as ...