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20162020
most citedNonparanormal Information Estimation

8 citations · 9 across the 2 of their papers we have counts for

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6 papers · 1 filter

math.ST2019

Nonparametric Density Estimation & Convergence Rates for GANs under Besov IPM Losses

Ananya Uppal, Shashank Singh, Barnabás Póczos

We study the problem of estimating a nonparametric probability density under a large family of losses called Besov IPMs, which include, for example, distances, tota…

math.ST2018

Nonparametric Density Estimation under Adversarial Losses

Shashank Singh, Ananya Uppal, Boyue Li +3

We study minimax convergence rates of nonparametric density estimation under a large class of loss functions called "adversarial losses", which, besides classical l…

math.ST2018

Minimax Estimation of Quadratic Fourier Functionals

Shashank Singh, Bharath K. Sriperumbudur, Barnabás Póczos

We study estimation of (semi-)inner products between two nonparametric probability distributions, given IID samples from each distribution. These products include relatively well-s…

math.ST2018

Minimax Distribution Estimation in Wasserstein Distance

Shashank Singh, Barnabás Póczos

The Wasserstein metric is an important measure of distance between probability distributions, with applications in machine learning, statistics, probability theory, and data analys…

math.ST20178 cited

Nonparanormal Information Estimation

Shashank Singh, Barnabás Pøczos

We study the problem of using i.i.d. samples from an unknown multivariate probability distribution to estimate the mutual information of . This problem has recently received…

math.ST2016

Exponential Concentration of a Density Functional Estimator

Shashank Singh, Barnabás P óczos

We analyze a plug-in estimator for a large class of integral functionals of one or more continuous probability densities. This class includes important families of entropy, diverge…