X. Song, K. Yang and M. Pavel, “Density Boosting for Gaussian Mixtures,” Neural Information Processing, Vol. 3316, 2004, pp. 508-515. http://dx.doi.org/10.1007/978-3-540-30499-9_78

has been cited by the following article:

• TITLE: Aggregating Density Estimators: An Empirical Study

  AUTHORS: Mathias Bourel, Badih Ghattas

  KEYWORDS: Machine Learning; Histogram; Kernel Density Estimator; Bagging; Boosting; Stacking

  JOURNAL NAME: Open Journal of Statistics, Vol.3 No.5, October 9, 2013

  ABSTRACT: Density estimation methods based on aggregating several estimators are described and compared over several simulation models. We show that aggregation gives rise in general to better estimators than simple methods like histograms or kernel density estimators. We suggest three new simple algorithms which aggregate histograms and compare very well to all the existing methods.