Scalable Methodologies for Optimizing Over Probability Distributions
Modern machine learning applications, such as generative modeling and probabilistic inference, demand a new generation of methodologies for optimizing over the space of probability distributions, where the optimization variable represents a weighted population of potentially infinitely many points....
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| Format: | Thesis |
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Massachusetts Institute of Technology
2024
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| Online Access: | https://hdl.handle.net/1721.1/156585 |