26 citations · 80 across the 15 of their papers we have counts for
10 papers · 1 filter
Testing Imprecise Hypotheses
Lucas Kania, Tudor Manole, Larry Wasserman +1
Many scientific applications involve testing theories that are only partially specified. This task often amounts to testing the goodness-of-fit of a candidate distribution while al…
Local Poisson Deconvolution for Discrete Signals
Shayan Hundrieser, Tudor Manole, Danila Litskevich +1
We analyze the statistical problem of recovering an atomic signal, modeled as a discrete uniform distribution , from a binned Poisson convolution model. This question is motivat…
Statistical Inference for Optimal Transport Maps: Recent Advances and Perspectives
Sivaraman Balakrishnan, Tudor Manole, Larry Wasserman
In many applications of optimal transport (OT), the object of primary interest is the optimal transport map. This map rearranges mass from one probability distribution to another i…
Stability Bounds for Smooth Optimal Transport Maps and their Statistical Implications
Sivaraman Balakrishnan, Tudor Manole
We study estimators of the optimal transport (OT) map between two probability distributions. We focus on plugin estimators derived from the OT map between estimates of the underlyi…
Randomized and Exchangeable Improvements of Markov's, Chebyshev's and Chernoff's Inequalities
Aaditya Ramdas, Tudor Manole
We present simple randomized and exchangeable improvements of Markov's inequality, as well as Chebyshev's inequality and Chernoff bounds. Our variants are never worse and typically…
Refined Convergence Rates for Maximum Likelihood Estimation under Finite Mixture Models
Tudor Manole, Nhat Ho
We revisit the classical problem of deriving convergence rates for the maximum likelihood estimator (MLE) in finite mixture models. The Wasserstein distance has become a standard l…
Plugin Estimation of Smooth Optimal Transport Maps
Tudor Manole, Sivaraman Balakrishnan, Jonathan Niles-Weed +1
We analyze a number of natural estimators for the optimal transport map between two distributions and show that they are minimax optimal. We adopt the plugin approach: our estimato…
Martingale Methods for Sequential Estimation of Convex Functionals and Divergences
Tudor Manole, Aaditya Ramdas
We present a unified technique for sequential estimation of convex divergences between distributions, including integral probability metrics like the kernel maximum mean discrepanc…
Uniform Convergence Rates for Maximum Likelihood Estimation under Two-Component Gaussian Mixture Models
Tudor Manole, Nhat Ho
We derive uniform convergence rates for the maximum likelihood estimator and minimax lower bounds for parameter estimation in two-component location-scale Gaussian mixture models w…
Minimax Confidence Intervals for the Sliced Wasserstein Distance
Tudor Manole, Sivaraman Balakrishnan, Larry Wasserman
Motivated by the growing popularity of variants of the Wasserstein distance in statistics and machine learning, we study statistical inference for the Sliced Wasserstein distance--…