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This paper is a tutorial and literature review on sampling algorithms.
Fitting a mixture distribution to data: tutorial
Ghojogh, Benyamin, Ghojogh, Aydin, Crowley, Mark, and Karray, Fakhri · 1901
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Feature selection and feature extraction in pattern analysis: A literature review
Ghojogh, Benyamin, Samad, Maria N, Mashhadi, Sayema Asif, Kapoor, Tania, Ali, Wahab, Karray, Fakhri, and Crowley, Mark · 1905
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Fisher and kernel Fisher discriminant analysis: Tutorial
Ghojogh, Benyamin, Karray, Fakhri, and Crowley, Mark · 1906
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On the likelihood that one unknown probability exceeds another in view of the evidence of two samples
Thompson, William R · 1933
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A generalization of sampling without replacement from a finite universe
Horvitz, Daniel G and Thompson, Donovan J · 1952
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Equation of state calculations by fast computing machines
Metropolis, Nicholas, Rosenbluth, Arianna W, Rosenbluth, Marshall N, Teller, Augusta H, and Teller, Edward · 1953
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Calculation of exact sampling distribution of ranges from a discrete population
Burr, Irving W · 1955
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Snowball sampling
Goodman, Leo A · 1961
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On simple random sampling with replacement
Pathak, PK · 1962
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Sufficiency and exponential families for discrete sample spaces
Andersen, Erling Bernhard · 1970
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Monte Carlo sampling methods using Markov chains and their applications
Hastings, W Keith · 1970
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Elements of sampling theory
Barnett, Vick · 1974
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Allocation in stratified sampling subsequent to preliminary test of significance
Sukhatme, BV and Tang, Victor KT · 1975
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Network sampling: Some first steps
Granovetter, Mark · 1976
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The foundations of survey sampling: a review
Smith, TMF · 1976
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Survey sampling in graphs
Frank, Ove · 1977
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Nonparametric statistical data modeling
Parzen, Emanuel · 1979
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Over-relaxation method for the Monte Carlo evaluation of the partition function for multiquadratic actions
Adler, Stephen L · 1981
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Stochastic relaxation, Gibbs distributions, and the Bayesian restoration of images
Geman, Stuart and Geman, Donald · 1984
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An introduction to the Ising model
Cipra, Barry A · 1987
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Hybrid Monte Carlo
Duane, Simon, Kennedy, Anthony D, Pendleton, Brian J, and Roweth, Duncan · 1987
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Power allocations: determining sample sizes for subnational areas
Bankier, Michael D · 1988
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Importance sampling for stochastic simulations
Glynn, Peter W and Iglehart, Donald L · 1989
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Survey sampling principles
Foreman, EK · 1991
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Adaptive rejection sampling for gibbs sampling
Gilks, Walter R and Wild, Pascal · 1992
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The weighted histogram analysis method for free-energy calculations on biomolecules. i. the method
Kumar, Shankar, Rosenberg, John M, Bouzida, Djamal, Swendsen, Robert H, and Kollman, Peter A · 1992
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Bootstrapping: A nonparametric approach to statistical inference
Mooney, Christopher F, Mooney, Christopher Z, Mooney, Christopher L, Duval, Robert D, and Duvall, Robert · 1993
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Monte Carlo matrix inversion and reinforcement learning
Barto, Andrew and Duff, Michael · 1994
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An introduction to the bootstrap
Efron, Bradley and Tibshirani, Robert J · 1994
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Estimation of regression coefficients when some regressors are not always observed
Robins, James M, Rotnitzky, Andrea, and Zhao, Lue Ping · 1994
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Fuzzy sets and fuzzy logic , volume 4
Klir, George and Yuan, Bo · 1995
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Bagging predictors
Breiman, Leo · 1996
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Stochastic processes , volume 2
Ross, Sheldon M, Kelly, John J, Sullivan, Roger J, Perry, William James, Mercer, Donald, Davis, Ruth M, Washburn, Thomas Dell, Sager, Earl V, Boyce, Joseph B, and Bristow, Vincent L · 1996
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Survey sampling
Schofield, William · 1996
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Introduction to Monte Carlo methods
Mackay, David John Cameron · 1998
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Exact sampling from a continuous state space
Murdoch, Duncan J and Green, Peter J · 1998
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Suppressing random walks in Markov chain Monte Carlo using ordered overrelaxation
Neal, Radford M · 1998
Cited alongside, same era.
Bayesian model averaging: a tutorial
Hoeting, Jennifer A, Madigan, David, Raftery, Adrian E, and Volinsky, Chris T · 1999
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Stochastic processes
Parzen, Emanuel · 1999
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Integer and combinatorial optimization , volume 55
A generalization of the adaptive rejection sampling algorithm
Martino, Luca and Míguez, Joaquín · 2011
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Elementary survey sampling
Scheaffer, Richard L, Mendenhall III, William, Ott, R Lyman, and Gerow, Kenneth G · 2011
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Monte Carlo methods in statistical physics , volume 7
Binder, Kurt, Ceperley, David M, Hansen, J-P, Kalos, MH, Landau, DP, Levesque, D, Mueller-Krumbhaar, H, Stauffer, D, and Weis, J-J · 2012
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Common survey sampling techniques
Hibberts, Mary, Johnson, R Burke, and Hudson, Kenneth · 2012
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Survey sampling
Tillé, Yves and Matei, A · 2012
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Monte Carlo Bayesian reinforcement learning
Wang, Yi, Won, Kok Sung, Hsu, David, and Lee, Wee Sun · 2012
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Wolsey, Laurence A and Nemhauser, George L · 1999
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Gibbs sampling
Gelfand, Alan E · 2000
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Survey sampling: Theory and methods, 2001
Nassiuma, Dankit K · 2001
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Annealed importance sampling
Neal, Radford M · 2001
Cited alongside, same era.
Optimal scaling for various metropolis-hastings algorithms
Roberts, Gareth O and Rosenthal, Jeffrey S · 2001
Cited alongside, same era.
The practice of statistics
Yates, Daniel S, Moore, David S, and Starnes, Daren S · 2002
Cited alongside, same era.
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Network sampling: From static to streaming graphs
Ahmed, Nesreen K, Neville, Jennifer, and Kompella, Ramana · 2013
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Monte Carlo methods in financial engineering , volume 53
Glasserman, Paul · 2013
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Monte Carlo methods
Hammersley, John · 2013
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Imbalanced learning: foundations, algorithms, and applications
He, Haibo and Ma, Yunqian · 2013
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Handbook of Monte Carlo methods , volume 706
Kroese, Dirk P, Taimre, Thomas, and Botev, Zdravko I · 2013
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Computational physics
Newman, Mark · 2013
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Monte Carlo statistical methods
Robert, Christian and Casella, George · 2013
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Elements of survey sampling , volume 15
Singh, Ravindra and Mangat, Naurang Singh · 2013
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Principles of random walk , volume 34
Spitzer, Frank · 2013
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Lecture on information theory, pattern recognition, and neural networks, University of Cambridge
MacKay, David · 2014
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The two-dimensional Ising model
McCoy, Barry M and Wu, Tai Tsun · 2014
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Optimising and adapting the metropolis algorithm
Rosenthal, Jeffrey S · 2014
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Coordinate descent algorithms
Wright, Stephen J · 2015
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Sampling and evaluation, a guide to sampling for program impact evaluation
Lance, PM and Hattori, A · 2016
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Non-probability sampling
Vehovar, Vasja, Toepoel, Vera, and Steinmetz, Stephanie · 2016
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Network sampling: From snowball and multiplicity to respondent-driven sampling
Heckathorn, Douglas D and Cameron, Christopher J · 2017
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Discriminator rejection sampling
Azadi, Samaneh, Olsson, Catherine, Darrell, Trevor, Goodfellow, Ian, and Odena, Augustus · 2018
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Log-concave sampling: Metropolis-hastings algorithms are fast!
Dwivedi, Raaz, Chen, Yuansi, Wainwright, Martin J, and Yu, Bin · 2018
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Variational rejection sampling
Grover, Aditya, Gummadi, Ramki, Lazaro-Gredilla, Miguel, Schuurmans, Dale, and Ermon, Stefano · 2018
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The Monte Carlo Method: Engineering Applications
Mazhdrakov, Metodi, Benov, Dobriyan, and Valkanov, Nikolai · 2018
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A tutorial on Thompson sampling
Russo, Daniel, Van Roy, Benjamin, Kazerouni, Abbas, Osband, Ian, and Wen, Zheng · 2018
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Reinforcement learning: An introduction
Sutton, Richard S and Barto, Andrew G · 2018
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The theory behind overfitting, cross validation, regularization, bagging, and boosting: tutorial
Ghojogh, Benyamin and Crowley, Mark · 2019
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Statistical analysis with missing data , volume 793
Little, Roderick JA and Rubin, Donald B · 2019
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Deligiannidis, George, Doucet, Arnaud, and Rubenthaler, Sylvain · 2020
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Introduction to survey sampling , volume 35
Kalton, Graham · 2020
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