Distributed Inference for Latent Dirichlet Allocation David Newman, Arthur Asuncion, Padhraic Smyth, Max Welling Department of Computer Science University of California, Irvine newman,asuncion,smyth,welling - Language classification - Document - PDFSEARCH.IO

First Page		Document Content
Date: 2008-10-31 18:54:19 Latent Dirichlet allocation Linear discriminant analysis Machine learning Parallel computing Algorithm Gibbs sampling Mixture model Speedup Expectation–maximization algorithm Statistics Statistical natural language processing Statistical classification		Distributed Inference for Latent Dirichlet Allocation David Newman, Arthur Asuncion, Padhraic Smyth, Max Welling Department of Computer Science University of California, Irvine newman,asuncion,smyth,welling @ics.uci.ed Add to Reading List Source URL: www.ics.uci.edu Download Document from Source Website File Size: 154,32 KB Share Document on Facebook

	Lecture 23, Thurs April 13: BBBV, Applications of Grover It’s great that we can get a quadratic speedup with Grover’s algorithm, but we were able to get an exponential speedup with Shor’s algorithm… So why can DocID: 1xVKf - View Document
	Lecture 27, Thurs April 27: Quantum Error Correction At the end of the last lecture, we discussed some of the difficulties with achieving a quantum speedup using currently available quantum computing devices, like D-Wave DocID: 1xVv9 - View Document
	SPNs: Network Reconstruction Theory and Speedup Using Neural Networks Balaji Prabhakar and Mendel Rosenblum Self-‐Programming Networks Research Group Stanf DocID: 1xTIn - View Document
	AsicBoost A Speedup for Bitcoin Mining Dr. Timo Hanke March 31, 2016 (rev. 5) Abstract. AsicBoost is a method to speed up Bitcoin mining by a factor of DocID: 1tUtd - View Document
	Kismet: Parallel Speedup Estimates for Serial Programs Donghwan Jeon Saturnino Garcia Chris Louie DocID: 1tIYD - View Document