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Learning Along the Edge of Deep Neural Networks

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개인저자Kabkab, Maya.
단체저자명University of Maryland, College Park. Electrical Engineering.
서명/저자사항Learning Along the Edge of Deep Neural Networks.
발행사항[S.l.] : University of Maryland, College Park., 2018
발행사항Ann Arbor : ProQuest Dissertations & Theses, 2018
형태사항157 p.
소장본 주기School code: 0117.
ISBN9780438144613
일반주기 Source: Dissertation Abstracts International, Volume: 79-12(E), Section: B.
Adviser: Rama Chellappa.
요약While Deep Neural Networks (DNNs) have recently achieved impressive results on many classification tasks, it is still unclear why they perform so well and how to properly design them. It has been observed that while training and testing deep net
요약In this dissertation, we analyze each of these individual conditions to understand their effects on the performance of deep networks. Furthermore, we devise mitigation strategies when the ideal conditions may not be met.
요약We, first, investigate the relationship between the performance of a convolutional neural network (CNN), its depth, and the size of its training set. Designing a CNN is a challenging task and the most common approach to picking the right archite
요약Next, we study the structure of the CNN layers, by examining the convolutional, activation, and pooling layers, and showing a parallelism between this structure and another well-studied problem: Convolutional Sparse Coding (CSC). The sparse repr
요약Then, we investigate three of the ideal conditions previously mentioned: the availability of vast amounts of noiseless and balanced training data. We overcome the difficulties resulting from deviating from this ideal scenario by modifying the tr
요약Finally, we consider the case where testing (and potentially training) samples are lossy, leading to the well-known compressed sensing framework. We use Generative Adversarial Networks (GANs) to impose structure in compressed sensing problems, r
일반주제명Computer science.
Electrical engineering.
Artificial intelligence.
언어영어
기본자료 저록Dissertation Abstracts International79-12B(E).
Dissertation Abstract International
대출바로가기http://www.riss.kr/pdu/ddodLink.do?id=T14997306

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