35 citations · 82 across the 23 of their papers we have counts for
3 papers · 1 filter
Product distribution learning with imperfect advice
Arnab Bhattacharyya, Davin Choo, Philips George John +1
Given i.i.d.~samples from an unknown distribution , the goal of distribution learning is to recover the parameters of a distribution that is close to . When belongs to th…
Learning High-dimensional Gaussians from Censored Data
Arnab Bhattacharyya, Constantinos Daskalakis, Themis Gouleakis +1
We provide efficient algorithms for the problem of distribution learning from high-dimensional Gaussian data where in each sample, some of the variable values are missing. We suppo…
Gaussian Mean Testing under Truncation
Clément L. Canonne, Themis Gouleakis, Yuhao Wang +1
We consider the task of Gaussian mean testing, that is, of testing whether a high-dimensional vector perturbed by white noise has large magnitude, or is the zero vector. This quest…