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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

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