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 8 of 8 for “"network compression"”.
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Topics in Sparsity and Compression: From High dimensional statistics to Overparametrized Neural Networks
… with categorical variables, and neural network compression. In the first chapter, motivated by problems in computational finance, we consider a framework for jointly learning time-varying covariance matrices under different structural assumptions (e.g., low-rank, sparsity or a …
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TwinDNN: A tale of two deep neural networks
Compression technologies for deep neural networks (DNNs), such as weight quantization, have been widely investigated to reduce the model size so that they can be implemented on hardware with strict resource restrictions. However, one major disadvantage of model compression is accuracy degradation. …
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Comparing Learned Representations Between Unpruned and Pruned Deep Convolutional Neural Networks
<p>While deep neural networks have shown impressive performance in computer vision tasks, natural language processing, and other domains, the sizes and inference times of these models can often prevent them from being used on resource-constrained systems. Furthermore, as these networks grow larger …
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Software and Hardware Co-design for Efficient Neural Networks
Deep Neural Networks (DNNs) offer state-of-the-art performance in many domains but this success comes at the cost of high computational and memory resources. Since DNN inference is now a popular workload on both edge and cloud systems, there is an urgent need to improve its energy efficiency. The …
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Practical Diagnostic Tools for Deep Neural Networks
… fields: interpreting and attacking deep neural networks. Both of these goals help to improve oversight of AI. However, existing techniques are often not competitive for practical debugging in real-world applications. This thesis is dedicated to identifying and addressing gaps between research …
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Analyzing The Community Structure Of Web-like Networks: Models And Algorithms
… investigates the community structure of web-like networks (i.e., large, random, real-life networks such as the World Wide Web and the Internet). Recently, it has been shown that many such networks have a locally dense and globally sparse structure with certain small, dense subgraphs occurring much …
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Unraveling the Structure and Assessing the Quality of Protein Interaction Networks with Power Graph Analysis
… of this endeavor is the compilation of complex networks of interacting proteins. Molecular biologists hope to understand life's complex molecular machines by studying these networks. This thesis addresses tree open problems centered upon their analysis and quality assessment. First, we introduce …
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Neural Network Prediction of Ultimate Compression After Impact Loads in Graphite-Epoxy Coupons from Ultrasonic C-Scan Images
… investigate how accurately an artificial neural network could predict the ultimate compressive loads of impact damaged 24-ply graphite-epoxy coupons from ultrasonic C-scan images. The 24-ply graphite-epoxy coupons were manufactured with bidirectional preimpregnated tape and cut into 21 coupons, 4 …