Asymptotic distribution and convergence rates of stochastic algorithms for entropic optimal transportation between probability measures
DOI10.1214/20-AOS1987zbMath1469.62218arXiv1812.09150OpenAlexW3034209236MaRDI QIDQ2039796
Publication date: 5 July 2021
Published in: The Annals of Statistics (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1812.09150
stochastic optimisationWasserstein distanceoptimal transportentropic regularizationconvergence of random variablesSinkhorn divergence
Asymptotic distribution theory in statistics (62E20) Asymptotic properties of nonparametric inference (62G20) Nonparametric estimation (62G05) Central limit and other weak theorems (60F05)
Related Items (1)
Uses Software
Cites Work
- Unnamed Item
- Limit laws of the empirical Wasserstein distance: Gaussian distributions
- A survey of the Schrödinger problem and some of its connections with optimal transport
- Geodesic PCA in the Wasserstein space by convex PCA
- On Hadamard differentiability in \(k\)-sample semiparametric models -- with applications to the assessment of structural relationships
- I-divergence geometry of probability distributions and minimization problems
- Notes on the Wasserstein metric in Hilbert spaces
- Large deviations and variational theorems for marginal problems
- Weak convergence rates for stochastic approximation with application to multiple targets and simulated annealing
- Tests of goodness of fit based on the \(L_2\)-Wasserstein distance
- Asymptotics for \(L_2\) functionals of the empirical quantile process, with applications to tests of fit based on weighted Wasserstein distances
- On the almost sure asymptotic behaviour of stochastic algorithm
- Semi-discrete optimal transport: a solution procedure for the unsquared Euclidean distance case
- Central limit theorems for entropy-regularized optimal transport on finite spaces and statistical applications
- Convergence of a Newton algorithm for semi-discrete optimal transport
- Central limit theorems for empirical transportation cost in general dimension
- A Smoothed Dual Approach for Variational Wasserstein Problems
- Adaptivity of averaged stochastic gradient descent to local strong convexity for logistic regression
- Scaling algorithms for unbalanced optimal transport problems
- Convex Color Image Segmentation with Optimal Transport Distances
- Polar factorization and monotone rearrangement of vector‐valued functions
- Acceleration of Stochastic Approximation by Averaging
- Nonparametric Validation of Similar Distributions and Assessment of Goodness of Fit
- Inference for Empirical Wasserstein Distances on Finite Spaces
- Fast Discrete Distribution Clustering Using Wasserstein Barycenter With Sparse Support
- The Phylogenetic Kantorovich–Rubinstein Metric for Environmental Sequence Samples
- An Algorithm for Optimal Transport between a Simplex Soup and a Point Cloud
- Empirical Regularized Optimal Transport: Statistical Theory and Applications
- A Stochastic Approximation Method
- Lp and almost sure rates of convergence of averaged stochastic gradient algorithms: locally strongly convex objective
- Optimal Transport
This page was built for publication: Asymptotic distribution and convergence rates of stochastic algorithms for entropic optimal transportation between probability measures