Fetching the paper…
Reading the bibliography…
Monte Carlo integration with variance reduction by means of control variates can be implemented by the ordinary least squares estimator for the intercept in a multiple linear regression model with the integrand as response and the control variates as covariates.
Gorman RP, Sejnowski TJ (1988) Analysis of hidden units in a layered network trained to classify sonar targets. Neural networks 1(1):75–89
1988
Earlier work this paper cites.
Marzolin G (1988) Polygynie du Cincle plongeur (Cinclus cinclus) dans les côtes de Lorraine. Oiseau et la Revue Francaise d’Ornithologie 58(4):277–286
1988
Earlier work this paper cites.
Lebreton JD, Burnham KP, Clobert J, Anderson DR (1992) Modeling survival and testing biological hypotheses using marked animals: a unified approach with case studies. Ecological monographs 62(1):67–118
1992
Earlier work this paper cites.
Avramidis AN, Wilson JR (1993) A splitting scheme for control variates. Operations Research Letters 14(4):187–198
1993
Earlier work this paper cites.
Tibshirani R (1996) Regression shrinkage and selection via the lasso. Journal of the Royal Statistical Society: Series B (Methodological) 58(1):267–288
1996
Earlier work this paper cites.
Newey WK (1997) Convergence rates and asymptotic normality for series estimators. Journal of econometrics 79(1):147–168
1997
Earlier work this paper cites.
Caflisch RE (1998) Monte Carlo and quasi-Monte Carlo methods. Acta Numerica 7:1–49
1998
Earlier work this paper cites.
Brooks SP, Catchpole EA, Morgan BJT (2000) Bayesian animal survival estimation. Statistical Science 15(4):357–376
2000
Earlier work this paper cites.
Glynn PW, Szechtman R (2002) Some new perspectives on the method of control variates. In: Monte Carlo and Quasi-Monte Carlo Methods 2000, Springer, pp 27–49
2000
Earlier work this paper cites.
Owen A, Zhou Y (2000) Safe and effective importance sampling. Journal of the American Statistical Association 95(449):135–143
2000
Earlier work this paper cites.
Rudin W (2006) Real and Complex Analysis. Tata McGraw-Hill Education
2006
Earlier work this paper cites.
Asuncion A, Newman D (2007) UCI Machine Learning Repository. Https://archive.ics.uci.edu/ml/index.php
2007
Earlier work this paper cites.
Bickel PJ, Ritov Y, Tsybakov AB (2009) Simultaneous analysis of Lasso and Dantzig selector. The Annals of Statistics 37(4):1705–1732
2009
Earlier work this paper cites.
van de Geer SA, Bühlmann P (2009) On the conditions used to prove oracle results for the Lasso. Electronic Journal of Statistics 3:1360–1392
2009
Earlier work this paper cites.
Gobet E, Labart C (2010) Solving BSDE with adaptive control variate. SIAM Journal on Numerical Analysis 48(1):257–277
2010
Cited alongside, same era.
Jie T, Abbeel P (2010) On a connection between importance sampling and the likelihood ratio policy gradient. In: Advances in Neural Information Processing Systems, pp 1000–1008
2010
Cited alongside, same era.
Pedregosa F, Varoquaux G, Gramfort A, Michel V, Thirion B, Grisel O, Blondel M, Prettenhofer P, Weiss R, Dubourg V, Vanderplas J, Passos A, Cournapeau D, Brucher M, Perrot M, Duchesnay E (2011) Scikit-learn: Machine learning in Python. Journal of Machine Learning Research 12:2825–2830
2011
Cited alongside, same era.
Horn RA, Johnson CR (2012) Matrix Analysis. Cambridge University Press
2012
Cited alongside, same era.
Hsu D, Kakade SM, Zhang T (2012) Random design analysis of ridge regression. In: Conference on learning theory, JMLR Workshop and Conference Proceedings, pp 9–1
Oates CJ, Girolami M, Chopin N (2017) Control functionals for Monte Carlo integration. Journal of the Royal Statistical Society: Series B (Statistical Methodology) 79(3):695–718
2017
Later among the works it cites.
Brosse N, Durmus A, Meyn S, Moulines É, Radhakrishnan A (2018) Diffusion approximations and control variates for MCMC. arXiv preprint arXiv:180801665
2018
Later among the works it cites.
Gower R, Le Roux N, Bach F (2018) Tracking the gradients using the hessian: A new look at variance reducing stochastic methods. In: International Conference on Artificial Intelligence and Statistics, PMLR, pp 707–715
2018
Later among the works it cites.
Javanmard A, Montanari A (2018) Debiasing the lasso: Optimal sample size for Gaussian designs. The Annals of Statistics 46(6A):2593–2622
2018
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
2012
Cited alongside, same era.
Belloni A, Chernozhukov V (2013) Least squares after model selection in high-dimensional sparse models. Bernoulli 19(2):521–547
2013
Cited alongside, same era.
Boucheron S, Lugosi G, Massart P (2013) Concentration Inequalities. Oxford University Press
2013
Cited alongside, same era.
Glasserman P (2013) Monte Carlo Methods in Financial Engineering, vol 53. Springer Science & Business Media
2013
Cited alongside, same era.
Owen AB (2013) Monte Carlo Theory, Methods and Examples
2013
Cited alongside, same era.
Wang C, Chen X, Smola AJ, Xing EP (2013) Variance reduction for stochastic gradient optimization. In: Advances in Neural Information Processing Systems, pp 181–189
2013
Cited alongside, same era.
Hsu D, Kakade SM, Zhang T (2014) Random design analysis of ridge regression. Foundations of Computational Mathematics 14(3):569–600
2014
Cited alongside, same era.
Ranganath R, Gerrish S, Blei D (2014) Black box variational inference. In: Artificial Intelligence and Statistics, pp 814–822
2014
Cited alongside, same era.
2018
Later among the works it cites.
Nott DJ, Drovandi CC, Mengersen K, Evans M, et al. (2018) Approximation of Bayesian predictive p p -values with regression ABC. Bayesian Analysis 13(1):59–83
2018
Later among the works it cites.
Portier F, Delyon B (2018) Asymptotic optimality of adaptive importance sampling. Advances in Neural Information Processing Systems 31:3134–3144
2018
Later among the works it cites.
South LF, Oates CJ, Mira A, Drovandi C (2018) Regularised zero-variance control variates for high-dimensional variance reduction. arXiv preprint arXiv:181105073
2018
Later among the works it cites.
Davis RA, do Rêgo Sousa T, Klüppelberg C (2019) Indirect inference for time series using the empirical characteristic function and control variates. Journal of Time Series Analysis
2019
Closest in time.
Jin C, Netrapalli P, Ge R, Kakade SM, Jordan M (2019) A short note on concentration inequalities for random vectors with subGaussian norm. arXiv preprint arXiv:190203736
2019
Closest in time.
Portier F, Segers J (2019) Monte Carlo integration with a growing number of control variates. Journal of Applied Probability 56:1168–1186
2019
Closest in time.
Zhang A, Brown LD, Cai TT (2019) Semi-supervised inference: General theory and estimation of means. The Annals of Statistics 47(5):2538–2566
2019
Closest in time.
Belomestny D, Iosipoi L, Moulines E, Naumov A, Samsonov S (2020) Variance reduction for Markov chains with application to MCMC. Statistics and Computing 30:973–997
2020
Closest in time.