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Robust and Scalable Algorithms for Bayesian Nonparametric Machine Learning

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자료유형	E-Book
개인저자	Roychowdhury, Anirban.
단체저자명	The Ohio State University. Computer Science and Engineering.
서명/저자사항	Robust and Scalable Algorithms for Bayesian Nonparametric Machine Learning.
발행사항	[S.l.] : The Ohio State University., 2017
발행사항	Ann Arbor : ProQuest Dissertations & Theses, 2017
형태사항	188 p.
소장본 주기	School code: 0168.
ISBN	9780438091412
일반주기	Source: Dissertation Abstracts International, Volume: 79-10(E), Section: B. Adviser: Srinivasan Parthasarathy.
요약	Bayesian nonparametric techniques provide a rich set of tools for modeling complex probabilistic machine learning problems. However the richness comes at the cost of significant complexity of learning and inference for large scale datasets, in a
요약	First, we develop fast inference algorithms for sequential models with Bayesian nonparametric priors using small-variance asymptotics, an emerging technique for obtaining scalable combinatorial algorithms from rich probabilistic models. We deriv
요약	We start the second section with a novel stick-breaking definition of a certain class of Bayesian nonparametric priors called gamma processes (GP), using its characterization as a completely random measure and attendant Poisson process machinery
요약	In the third section, we use concepts from statistical physics to develop a robust Monte Carlo sampler that efficiently traverses the parameter space. Built on the Hamiltonian Monte Carlo framework, our sampler uses a modified Nose-Poincare Hami
요약	We continue with an L-BFGS optimization algorithm on Riemannian manifolds that uses stochastic variance reduction techniques for fast convergence with constant step sizes, without resorting to standard linesearch methods, and provide a new conve
요약	We finish with a novel technique for learning the mass matrices in Monte Carlo samplers obtained from discretized dynamics that preserve some energy function, by using existing dynamics in the sampling step of a Monte Carlo EM framework, and lea
일반주제명	Computer science.
언어	영어
기본자료 저록	Dissertation Abstracts International79-10B(E). Dissertation Abstract International
대출바로가기	http://www.riss.kr/pdu/ddodLink.do?id=T15000214