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Description:: Recently, machine learning and deep learning, which have made many theoretical and empir- ical breakthroughs and is widely applied in various fields, attract a great number of researchers and practitioners. They have become one of the most popular research directions and plays a sig- nificant role in many fields, such...
Keyword:: Algorithm Design, Deep Learning, Optimization, and Machine Learning
Subject:: Applied mathematics and Operations research
Creator:: Fang, Biyi
Owner:: Scholarly Digital Publishing
Language:: en
Date Uploaded:: 02/02/2022
Date Created:: 2021-01-01
Resource Type:: Dissertation
Alternate Identifier:: http://dissertations.umi.com/northwestern:15817 and etdadmin_upload_855647

Description:: While optimization has received much attention in the machine learning community, most of them consider unconstrained supervised learning models such as neural networks and support vector machine. In this dissertation, we introduce a new class of optimization problems called scale invariant problems that include interesting unsupervised learning models such as...
Keyword:: Power Iteration, PCA, Optimization, Machine Learning, Scale Invariance, and KL-NMF
Subject:: Applied mathematics and Operations research
Creator:: Kim, Cheolmin
Owner:: Scholarly Digital Publishing
Language:: en
Date Uploaded:: 02/01/2021
Date Created:: 2020-01-01
Resource Type:: Dissertation
Alternate Identifier:: http://dissertations.umi.com/northwestern:15139 and etdadmin_upload_744178

Description:: This thesis focuses on applications of recurrent neural networks (RNNs) for three aspects of sequential classification. In the first chapter, a novel method to generate synthetic minority data generation to improve imbalanced classification is discussed. Generative Adversarial Networks (GANs) have been used in many different applications to generate realistic synthetic...
Keyword:: Explainability, Recurrent Neural Networks, and Machine Learning
Subject:: Applied mathematics
Creator:: Ger, Stephanie Kwang-Yu
Owner:: Scholarly Digital Publishing
Language:: en
Date Uploaded:: 02/01/2021
Date Created:: 2020-01-01
Resource Type:: Dissertation
Alternate Identifier:: http://dissertations.umi.com/northwestern:15394 and etdadmin_upload_780385

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