A Framework for Probability Density Estimation

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How researchers see this paper

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Kernel Mean Embedding of Distributions: A Review and Beyonds (2016, background): “It turns out that this interpretation coincides with the one given in Shawe-Taylor and Dolia (2007). Specifically, let H be a set of functions and Π be a probability distribution over H .”
A Kernel Method for the Two-Sample-Problem (2006, methodology): “uted empirically on the basis of 200 samples, using a Gaussian kernel with σ= 0.2. 21 Gretton, Borgwardt, Rasch, Sch¨olkopf and Smola 7.4 Kernel Statistics Using a Distribution over Witness Functions Shawe-Taylor and Dolia (2007) deﬁne a distance between distributions as follows: let H be a set of f”
Robust kernel density estimation (2008, background): “Shawe-Taylor & Dolia (2007) provide a refined theoretical treatment of this approach.”
A Kernel Two-Sample Test (2012, background): “Shawe-Taylor and Dolia (2007) define a distance between distributions asfollows: letH be a set of functions onX andr be a probability distribution overH.”
Understanding bag-of-words model: a statistical framework (2010, methodology): “To bound the difference between sij and sij , we follow the analysis (Shawe-Taylor and Dolia, 2007) by viewing Ei[f(x)]Ej [f(x)] as a mapping, denoted by g : F 7→ R+, i.”
Tailoring density estimation via reproducing kernel moment matching (2008, methodology): “Our work is related to the density estimators of Vapnik & Mukherjee (2000) and Shawe-Taylor & Dolia (2007).”