Advances in Bayesian inference and stable optimization for large-scale machine learning problems
A core task in machine learning, and the topic of this thesis, is developing faster and more accurate methods of posterior inference in probabilistic models. The thesis has two components. The first explores using deterministic methods to improve the efficiency of Markov Chain Monte Carlo (MCMC) alg...
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| Language: | English |
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2019
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| Online Access: | https://doi.org/10.7916/D8RF7BZP |