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Rejection sampling
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1	Microsoft PowerPoint - class-7-out.ppt [Compatibility Mode] Add to Reading List Source URL: people.cs.pitt.edu Language: English - Date: 2014-09-16 19:24:19 Mathematical analysis Statistics Probability Probability distributions 0.999... 1 Normal distribution Rejection sampling Expected value
2	JMLR: Workshop and Conference Proceedings vol 40:1–26, 2015 Escaping the Local Minima via Simulated Annealing: Optimization of Approximately Convex Functions Alexandre Belloni The Fuqua School of Business, Duke Univer Add to Reading List Source URL: jmlr.org Language: English - Date: 2015-07-20 20:08:35 Mathematical analysis Analysis Mathematics Convex analysis Logarithmically concave function Convex function Central limit theorem Normal distribution Convex optimization Expected value Distribution Rejection sampling
3	Exact and Efficient Generation of Geometric Random Variates and Random Graphs Karl Bringmann1 and Tobias Friedrich2 1 Max-Planck-Institut f¨ Add to Reading List Source URL: people.mpi-inf.mpg.de Language: English - Date: 2016-01-03 06:45:52 Mathematics Computational complexity theory Graph theory Analysis of algorithms NP-complete problems Probabilistic complexity theory Combinatorics Randomized algorithm Rejection sampling NP Independent set Poisson distribution
4	2014 IEEE International Conference on Acoustic, Speech and Signal Processing (ICASSP) INDEPENDENT DOUBLY ADAPTIVE REJECTION METROPOLIS SAMPLING Luca Martino? , Jesse Read† , David Luengo‡ ? Add to Reading List Source URL: users.ics.aalto.fi Language: English - Date: 2014-08-22 09:13:11 Statistics Monte Carlo methods Computational statistics Markov chain Monte Carlo Statistical theory Non-uniform random numbers Rejection sampling MetropolisHastings algorithm Stochastic simulation Gibbs sampling
5	1 Improved Adaptive Rejection Metropolis Sampling Algorithms Luca Martino† , Jesse Read† , David Luengo‡ † Add to Reading List Source URL: arxiv.org Language: English - Date: 2012-10-09 00:12:52 Monte Carlo methods Markov chain Monte Carlo Non-uniform random numbers Rejection sampling MetropolisHastings algorithm Limit of a function
6	Sampling for Approximate Inference in Continuous Time Bayesian Networks Yu Fan Christian R. Shelton Add to Reading List Source URL: rlair.cs.ucr.edu Language: English - Date: 2011-01-19 19:25:42 Monte Carlo methods Stochastic simulation Estimation theory Robot control Markov models Importance sampling Particle filter Probability distribution Bayesian network Exponential distribution Rejection sampling Expectationmaximization algorithm
7	Lab Exercise: The rejection method of generating samples GEOS 627: Inverse Problems and Parameter Estimation, Carl Tape Last compiled: February 5, 2015 Overview • The purpose of this exercise is to understand one parti Add to Reading List Source URL: www.giseis.alaska.edu Language: English - Date: 2015-02-05 15:25:16 Monte Carlo methods Non-uniform random numbers Linear algebra MATLAB Mathematical software Rejection sampling Limit of a function
8	2013 IEEE International Conference on Computer Vision Slice Sampling Particle Belief Propagation Oliver Müller, Michael Ying Yang, and Bodo Rosenhahn Institute for Information Processing (TNT), Leibniz University Hanno Add to Reading List Source URL: www.tnt.uni-hannover.de Language: English - Date: 2016-08-02 06:36:10 Monte Carlo methods Markov chain Monte Carlo Non-uniform random numbers Probability distributions Computational statistics MetropolisHastings algorithm Rejection sampling Gibbs sampling Normal distribution Slice sampling Uniform distribution
9	A Level-set Hit-and-run Sampler for Quasi-Concave Distributions Shane T. Jensen and Dean P. Foster Department of Statistics, The Wharton School, University of Pennsylvania Abstract Add to Reading List Source URL: www-stat.wharton.upenn.edu Language: English - Date: 2014-05-24 19:58:02 Monte Carlo methods Markov chain Monte Carlo Non-uniform random numbers Probability distributions Computational statistics Gibbs sampling Rejection sampling MetropolisHastings algorithm Slice sampling Bayesian network Quasiconvex function Normal distribution
10	Distributed and Adaptive Darting Monte Carlo through Regenerations Sungjin Ahn Department of Computer Science University of California, Irvine Irvine, CA, USA Add to Reading List Source URL: www.ics.uci.edu Language: English - Date: 2013-04-11 10:50:54 Markov models Markov chain Monte Carlo Computational statistics Markov processes Markov chain Metropolis–Hastings algorithm Rejection sampling Mixture model Random walk Statistics Probability and statistics Monte Carlo methods