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2 votes
1 answer
173 views

Is there an analogue of transportation-cost inequality under a weighted Log-Sobolev Inequality?

It is known that under the Log-Sobolev Inequality for $\pi$, i.e., if for all $\rho$, $$H_\pi(\rho):=\int \rho(x)\log\frac{\rho(x)}{\pi(x)}dx \leq \frac{1}{2\beta}\int \rho(x)\left\|\nabla \log\frac{\...
user_qj's user avatar
  • 21
2 votes
0 answers
123 views

Closure of finite support measures in the Wasserstein metric

This is a follow-up question to this question: Closure Wasserstein for pointmasses Let $(X,d)$ be a metric space, and let $W_1(X)$ be the space of probability measures $\mu$ on $X$ having finite first ...
Alain Valette's user avatar
0 votes
1 answer
86 views

Is integration against an indicator Wasserstein-Continuous

Let $\mathcal{P}_p(X)$ denote the Wasserstein space over a compact metric space $X$, and $1\leq p<\infty$. Fix a non-empty closed subset $C\subseteq X$. Then is the map: $$ \mathbb{P} \mapsto \...
ABIM's user avatar
  • 5,405
2 votes
0 answers
302 views

Simplify Kantorovich–Rubinstein duality when distributions share a common marginal

Consider the product of two metric spaces $X\times Y$, and two probability distributions $\mu$ and $\nu$ on this product space. By the Kantorovich-Rubinstein duality, I can write the Wasserstein-1-...
joemrt's user avatar
  • 53
1 vote
1 answer
241 views

Continuity of pushforward operation

Let $X$ and $Y$ be compact metric spaces and let $f,g:X\rightarrow Y$ be $\epsilon$-uniformly close; i.e.: $$ \sup_{x \in X} d_Y(f(x),g(x))<\epsilon. $$ Then, are their push-forwards close in ...
ABIM's user avatar
  • 5,405
3 votes
1 answer
385 views

Are there any results on concentration bounds of Wasserstein distances between empirical measures?

I know there are concentration bounds on $W(\mu,\hat{\mu})$ where $\mu$ and $\hat{\mu}$ are true and empirical distributions respectively, but is there anything out there on $W(\mu,\nu)$ versus $W(\...
Kashif's user avatar
  • 383
0 votes
0 answers
87 views

How does one define weak convergence of probability measures in $L^{\infty}(\Omega)$?

I am reading the following article and on page 9/17 (above Eqn (4.9)) the authors state that if $\gamma_{\epsilon_k}|\_G_{\delta}\times \Omega\to \gamma|\_G_{\delta}\times \Omega$ as $\epsilon_k\to 0$ ...
Student's user avatar
  • 547
0 votes
1 answer
141 views

Arbitrarily bad rates of convergence in Wasserstein metric

Suppose $W_p(\mu_n,\mu)\to 0$ and $d(E(\mu_n),E(\mu))<r_n$. Here, $W_p$ is the $p$th-order Wasserstein distance (with respect to the metric $d$) and $\mu_n,\mu$ are probability measures on some ...
user489304's user avatar
8 votes
4 answers
2k views

How to interpret couplings in optimal transport?

Let $\mu$ and $\nu$ be two measures on some (at least measurable) space $X$. In optimal transport theory, Monge's problem to $$ \text{minimize} \quad \int c(x,T(x))\mu(dx) \quad \text{over measurable ...
vaoy's user avatar
  • 309
1 vote
0 answers
96 views

Relationship between Wasserstein projections and metric projections in a linear space

Let $(X,d)$ be a metric space, $x\in X$, and $Y\subset X$ is a closed set. Assume that $X$ is also a real vector space, so that we can form linear combinations over $\mathbb{R}$, but I do not assume ...
user489304's user avatar
5 votes
2 answers
953 views

Comparison of Information and Wasserstein Topologies

There are many possible metrics one can place on the space of Gaussian probability measures on $\mathbb{R}^n$, with strictly positive definite co-variance matrices. Let's denote this space by $X$. I'...
Catologist_who_flies_on_Monday's user avatar
1 vote
1 answer
1k views

Closed-form upper-bounds for Wasserstein distance between finite measures

Let $x_1,\dots,x_n,y_1,\dots,y_n\in \mathbb{R}$ and such that $x_i\neq x_j$ and $y_i\neq y_j$ if $i\neq j$. Let $a,b$ be elements of the probability n-simplex. Define the measures $\mu\triangleq \...
ABIM's user avatar
  • 5,405
0 votes
1 answer
267 views

Intersection of projection of sets

Suppose that we have two arbitrary sets $\mathcal{X}$, $\mathcal{Y}$ and are given a function $c : \mathcal{X} \times \mathcal{Y} \rightarrow \mathbb{R}$ Consider the following inequality for ...
qp212223's user avatar
  • 143
1 vote
0 answers
56 views

Moduli of continuity and Wasserstein differentiability of functions between measures

Let $X=\mathbb{R}^n$; I am also interested in the general case $X$ is a metric space but for simplicity let's focus on Euclidean space. Let $\mathcal{P}(X)$ denote the space of Borel probability ...
JeffHolder's user avatar
2 votes
1 answer
228 views

Ideas on how to prove Pythagorean identity involving Wasserstein distances?

I conjectured earlier that if $P$ and $Q$ were two probability measures, then we could show $$W^2(P,Q) = \min_{T} [d^2(P,T_{\#}P) + W^2(T_{\#}P,Q)]$$ where $W^2(P,Q)$ denotes the squared Wasserstein-2 ...
Kashif's user avatar
  • 383
14 votes
2 answers
892 views

Do distance functionals separate probability measures?

Let $(\Omega,d)$ be a compact metric space and $\mathcal P(\Omega)$ its space of Borel probability measures. Let $D=\{ d_p\mid p\in\Omega\}$ where $d_p(x)=d(p,x)$ be the set of all "distance ...
Christian Bueno's user avatar
3 votes
1 answer
987 views

About the metrizability of the space of Probability measures $\mathcal{P}(S)$

It is often proved in Books that the space of Probability measures $\mathcal{P}(S)$ on a Polish metric space $(S,\rho)$ endowed with the weak/narrow topology induced by declaring it to be be the ...
vaoy's user avatar
  • 309
1 vote
0 answers
113 views

Metrics on the space of distributions in terms of p.d.fs

If two probability distributions (on the same measure space) are s.t they have p.d.fs and the $L^1$ distance between the p.d.f.s is large, then is there a choice of a ``nice" metric $d_{\rm ...
gradstudent's user avatar
  • 2,246
2 votes
0 answers
328 views

Explicit formula for this distance between positive semi-definite matrices?

Let $A$ and $B$ in $\mathbb{R}^{d\times d}$ be positive semi-definite (psd) matrices and let $d\tau$ be the uniform probability distribution on the unit sphere $\mathbb{S}^{d-1}$ in $\mathbb{R}^d$. I ...
Lénaïc Chizat's user avatar
3 votes
0 answers
163 views

A new "adversarial" Wasserstein distance?

Let us consider $\mu_1, \mu_2$ and $\mu_3$ three probability measures living on $[0,1]^{k_1}, [0,1]^{k_2}$ and $[0,1]^k$respectively, with $k_1 +k_2=k$. Let us denote by $\Gamma(\mu,\nu)$ the set of ...
Gilles Mordant's user avatar
1 vote
1 answer
719 views

Transport of measure

Let's disintegrate $\mu$ and $\nu$, two probabilities on $\mathbb{R}^{d}$ , according to $$ \pi_{k} (x_{1},...,x_{d}) = (x_{k},...,x_{d}) $$ We get a family of measures and each measure $\mu_{k,d}^{+...
CechMS's user avatar
  • 179
0 votes
1 answer
223 views

A problem with the dual form of semi-discrete optimal transport

Consider the uniform distribution $\lambda$ on $[0,1]$, and a point measure $\rho$ with density $\frac{1}{2} (\delta_{x_1} + \delta_{x_2})$, where we have $0\le x_1 \le x_2 < 1/2$. If our cost is ...
occassional user's user avatar
6 votes
2 answers
763 views

How to control Wasserstein distance in terms of characteristic function

Let $\mathcal P(\Omega)$ be the set of probability measures supported on some compact subset $\Omega\subset\mathbb R^d$. For $\mu\in\mathcal P(\Omega)$, denote by $F_{\mu}$ its characteristic function,...
user avatar
0 votes
1 answer
211 views

Relationship between a certain binary optimal transport and total-variation of modified distributions

Let $\mathcal X$ be a Polish space, and let $(N_x)_{x \in \mathcal X}$ be a system of closed neighborhoods in $\mathcal X$. Define $\Omega := \{(x,x') \in \mathcal X^2 \mid N_x \cap N_{x'} = \emptyset\...
dohmatob's user avatar
  • 6,853
1 vote
0 answers
81 views

Empirical estimation of $\inf_{\gamma \in \Pi(\mu,\nu)}\gamma(\Omega)$, given i.i.d samples from $\mu$ and $\nu$

Let $\mathcal X$ be a Polish space and $\Omega \subseteq \mathcal X^2$ be open. Let $\mu$ and $\nu$ be probability measures, and consider the quantity $c_\Omega(\mu,\nu)$ defined by $$ c_\Omega(\mu,\...
dohmatob's user avatar
  • 6,853
0 votes
0 answers
75 views

Optimizer of a semi-discrete optimal transport problem

Provided two probability distributions $\mu(dx)=\rho(x)dx$ and $\nu(dx)=\sum_{i=1}^n p_i\delta_{y_i}(dx)$ that are supported on some measurable set $\Omega\subset\mathbb R^d$, we consider the semi-...
user avatar
1 vote
0 answers
176 views

Rate of convergence of empirical distribution with respect to Wasserstein distance induced by binary cost function

Let $\mathcal X=(\mathcal X, d)$ be a Polish space (i.e complete metric space), and let $\Omega$ be a non-empty subset. Consider the binary cost function $c_\Omega$ on $\mathcal X^2$ defined by $c_\...
dohmatob's user avatar
  • 6,853
1 vote
2 answers
889 views

Simplify Wasserstein distance between Gaussians with binary cost function

Let $\mu_1$ and $\mu_2$ be 1D gaussian distributions with means $m_1$ and $m_2$ respectively and common variance $\sigma$. Let $\Omega$ be a closed subset of $\mathbb R^2$, and consider the cost ...
dohmatob's user avatar
  • 6,853
3 votes
1 answer
170 views

Reformulation as optimization on probability distributions

This is a "soft" question, in the sense that I'm looking for historical remarks and general commentary rather than a definite answer. For compact $X \in R^n$ and $f : R^n \to R$ consider the problem ...
golden-rabbit's user avatar
1 vote
1 answer
242 views

Barycenter Map on Wasserstein Space

Let $(X,d)$ be a complete separable metric space, $P_1(X,d)$ be the set of Radon probability measures on $X$ satisfying $$ P_1(X,d)\triangleq \left\{ \nu:\,(\exists x_0\in X)\, \int_{x\in X} d(x,x_0)d\...
ABIM's user avatar
  • 5,405
2 votes
1 answer
194 views

Strong convexity of internal energy with respect to Wasserstein metric

It is well known that the internal energy (see, e.g., Definition 3.32 in and Proposition 3.33 in 1) is geodesically convex with the 2-Wasserstein distance. I was wondering under what condition, the ...
O. Richard's user avatar
4 votes
1 answer
596 views

Monge-Kantorovich duality with a $\{0,1\}$ cost function

Consider the usual Monge-Kantorovich transportation problem where $X$ and $Y$ are Polish spaces, $\mu$ and $\nu$ are probability measures on $X$ and $Y$, and $c:X\times Y \to \mathbb{R}^+ \cup \{+\...
Tom Solberg's user avatar
  • 4,049
3 votes
2 answers
165 views

continuity/ measurablity of optimal transport

given polish space $(X,d)$, consider weak* topology of probability. optimal transport of probability $u,v$ is defined by $\pi(u,v)$ such that $\pi(u,v)$ minimizes: $\{\int d(x,y) d \pi(dx,dy): \pi \...
jason's user avatar
  • 553
2 votes
1 answer
257 views

Reference Request: 2-Wasserstein Metric on Wiener Space

Suppose that X is the subspace of the set of probability measures on the classical Wiener space $C[0,T]$, for some $T>0$, comprised of Gaussian measures. In the finite-dimensional setting, the ...
ABIM's user avatar
  • 5,405
1 vote
1 answer
1k views

Monotonicity, Convexity, and Smoothness of the KL-Divergence between Two Brownian Motions with Different Initializers

We consider the two distributions $$ p_t = p_0 * N(0, tI),\quad q_t = q_0 * N(0, t I), $$ where $*$ denotes the convolution between two densities, while $p_0$ and $q_0$ have the same mean and ...
Minkov's user avatar
  • 1,127
5 votes
0 answers
244 views

Distribution of point knowing target in optimal matching

I am a young PhD student in statistics. Recently, papers (Ambrosio, Stra and Trevisan; Talagrand; Ledoux to cite but a few) tackled the problem of finding the expected cost in an optimal matching, ...
Gilles Mordant's user avatar
0 votes
0 answers
103 views

Expectation of maximal Wasserstein distance between empirical distribution and a pdf

Let $P$ be a continuous probability distribution on $R^d$, $X$ the random variable $\sim P$, and $ \hat{X}$ be n i.i.d samples drawn according to $P$. We have another variable $\mu \in S^{d-1}$. Do ...
Will Cai's user avatar
  • 109
3 votes
1 answer
311 views

Kantorovich duality with pseudometrics

The usual framework for the Kantorovich duality in optimal transport theory uses Polish spaces as ground spaces for the distributions that should be transported. Are there results available that ...
Markus Holzleitner's user avatar
3 votes
1 answer
202 views

Is there a coupling that induces a given coupling via a transition kernel?

Let $X,Y$ be two measurable spaces, $\mu,\nu$ two probability measures on $X$, and $\kappa$ a transition kernel from $X$ to $Y$. Define $\tilde\mu(dy)=\int_X\kappa(dy|x)\mu(dx)$ and $\tilde\nu(dy)=\...
S.Surace's user avatar
  • 1,675
4 votes
2 answers
415 views

Effect of perturbing the atoms of a measure on the Wasserstein distance

Let $(X,d)$ be a metric space, $x_1,\ldots,x_N\in X$ and $x_1',\ldots,x_N'\in X$ be atoms, and $G=\sum_{i=1}^Np_i\delta_{x_i}$, $G'=\sum_{i=1}^Np_i'\delta_{x_i}$, and $G''=\sum_{i=1}^Np_i'\delta_{x_i'}...
JohnA's user avatar
  • 710
2 votes
1 answer
210 views

Controlling Mean Difference Between Product and Joint Distributions Using Optimal Transportation

Suppose we have nonindependent random variables $X \sim P$ and $Y \sim Q$, where $P$ and $Q$ denote their marginal distributions. We are interested in upper bounding $$ |\mathbf{E}_{X, Y\sim P \...
Minkov's user avatar
  • 1,127
5 votes
1 answer
396 views

Universal decay rate of the Fisher information along the heat flow

I'm looking for a reference for the following fact: In the torus $\mathbb T^d$ let me denote by $u_t=u(t,x)$ the (unique, distributional) solution of the heat equation $$ \partial_t u=\Delta u $$ ...
leo monsaingeon's user avatar
3 votes
1 answer
2k views

Closed-form formula for Wasserstein distance between uniform discrete distribution and discrete distribution with same support

Let $x_1,\ldots,x_n$ be $n \ge 1$ distinct points in $\mathbb R^d$ and consider two discrete distributions on these points $\mu = (1/n)\sum_{i=1}^n\delta_{x_i}$, and $\nu = \sum_{i=1}^n\nu_i\delta_{...
dohmatob's user avatar
  • 6,853
2 votes
1 answer
1k views

Wasserstein interpolation between two probability measures on a metric space

Question 1 Given probability measures $\mu$ and $\nu$ on the same metric space $X=(X,d)$, and $\alpha \in [0, 1]$, is it always possible to find another probability measure $\lambda_\alpha$ on $X$ ...
dohmatob's user avatar
  • 6,853
3 votes
0 answers
243 views

Parametric distances on product spaces of measures

Disclaimer: Please excuse my loose language. I'm neither an expert in geometry nor probability. Please ask for clarification if something appears unclear or awkward to you. Let $X$ be a topological ...
dohmatob's user avatar
  • 6,853
2 votes
1 answer
289 views

On semi-discrete Wasserstein distance

Let $\mu(dx)=\sum_{i=1}^np_i\delta_{x_i}(dx)$ and $\nu(dy)=\rho(y)dy$ be two probability measures on $\mathbb R^d$, where $\nu$ has a bounded support. Consider the $2-$Wasserstein distance below: $$...
user111097's user avatar
4 votes
0 answers
757 views

Tangent space and gradient on subspace of Wasserstein space given by finitely supported measures

Let $\mathcal{P}_2(M)$ be the 2-Wasserstein space over some Riemannian manifold $(M,g)$ (connected, complete, and without boundary). Let $\mathcal{FP}_2(M,n)$ be the subspace of probability measures ...
S.Surace's user avatar
  • 1,675
4 votes
1 answer
2k views

Earth movers distance (EMD) between two multivariate normals. Is it negative definite distance?

I was looking at the closed form formula for 2-Wassersteins distance for multivariate normal distribution on Wikipedia. https://en.wikipedia.org/wiki/Wasserstein_metric#Normal_distributions It has a ...
user24318's user avatar
  • 141
2 votes
1 answer
309 views

Density in Wasserstein space

I am wondering whether the following result is true: Let $\mathcal W_p(\mathbb R^d)$ be the Wasserstein space of order $p$ and let $\eta$ and $\gamma$ be two probability measures in $\mathcal W_p(\...
Ryan's user avatar
  • 325
10 votes
1 answer
274 views

Cutting a Gaussian in two pieces that are maximally separated in the Wasserstein metric

Denote the standard Gaussian probability measure on $\mathbb R^n$ by $\gamma$. We partition $\mathbb R^n$ into two sets $A$ and $A^c$ such that $\gamma(A) = \gamma(A^c) = 1/2$. Denote by $\gamma_{A}$...
VSJ's user avatar
  • 1,034