4 citations · 12 across the 8 of their papers we have counts for
Showing 2021Show all
3 papers · 1 filter
stat.ML2021★ 2 cited
Outlier-Robust Optimal Transport: Duality, Structure, and Statistical Analysis
Sloan Nietert, Rachel Cummings, Ziv Goldfeld
The Wasserstein distance, rooted in optimal transport (OT) theory, is a popular discrepancy measure between probability distributions with various applications to statistics and ma…
cs.LG2021★ 1 cited
Learning with Comparison Feedback: Online Estimation of Sample Statistics
Michela Meister, Sloan Nietert
We study an online version of the noisy binary search problem where feedback is generated by a non-stochastic adversary rather than perturbed by random noise. We reframe this as ma…
math.ST2021
Smooth -Wasserstein Distance: Structure, Empirical Approximation, and Statistical Applications
Sloan Nietert, Ziv Goldfeld, Kengo Kato
Discrepancy measures between probability distributions, often termed statistical distances, are ubiquitous in probability theory, statistics and machine learning. To combat the cur…