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Questions tagged [optimal-transportation]

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7 votes
3 answers
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Hyperbolic space embeds into Wasserstein space

Fix a positive integer $n$, let $\mathbb{H}^n$ be the $n$-dimensional hyperbolic space, $r>0$, $x\in \mathbb{H}^n$ and consider the closed (compact) geodesic ball $B_{\mathbb{H}^n}(x,r)$. Are ...
Carlos_Petterson's user avatar
1 vote
0 answers
71 views

Hyperplanes which equalize the Radon transforms of two distributions

Let $p_1$ and $p_2$ be "nice" probability densities on $\mathbb R^m$, for example the densities of a multivariate Gaussians $N(\mu_1,\Sigma)$ and $N(\mu_2,\Sigma)$ with common covariance ...
dohmatob's user avatar
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1 vote
1 answer
64 views

Expectation of a function according to a family of distributions

Consider a family of smooth, atomless CDFs, $F_x(\cdot)$, for each $x \in \mathbb R$. Suppose that $F_x(\cdot)$ are FOSD ranked in $x$. That is, for any $x, x'$ such that $x \ge x'$, $F_x(\cdot) \le ...
avk255's user avatar
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4 votes
1 answer
360 views

Measurability of Markov kernel wrt the Borel $\sigma$-algebra generated by the weak topology

Consider two Polish metric probability spaces $(\mathcal{A}, \Sigma_\mathcal{A})$ and $(\mathcal{B}, \Sigma_\mathcal{B})$, endowed with their Borel $\sigma$-algebras. Denote as $\mathcal{P}_\mathcal{B}...
ECL's user avatar
  • 345
1 vote
0 answers
37 views

Sufficient condition for an $n$-tuple to be a convex conjugate

We say $(f_1,f_2,\dotsc,f_N)$ is a convex conjugate if for any $i=1,2,\dotsc,N$ and any $x_i\in\Bbb R^d$, we have: $$f_i(x_i)=\sup\left\{\sum_{k=1}^{N}\sum_{j=k+1}^N x_k x_j - \sum_{j=1,j\neq i}^N f_j(...
Silentmovie's user avatar
1 vote
2 answers
283 views

Building the Wasserstein space by pushforwards

Let $\mathbb{R}^d$ denote the $d$-dimensional Euclidean space, $\mathcal{W}_2(\mathbb{R}^d)$ denote the $2$-Wasserstein space with respect to the $d$-dimensional Euclidean space $\mathbb{R}^d$. Let $...
ABIM's user avatar
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2 votes
0 answers
82 views

Estimate of Wasserstein distance and flow of vector fields under particular assumptions

Let $\mu$ be a compactly supported absolutely continuous probability measure. Let $v,u$ be Lipschitz vector fields. For a vector field $w$ recall that $\Phi_t^w$ denotes its flow. A classical estimate ...
Jun's user avatar
  • 303
1 vote
1 answer
306 views

When are Wasserstein spaces $CAT(\kappa)$?

Let $(X,d)$ be a complete and separable metric space and, for $1\leq p<\infty$, let $(\mathcal{P}_p(X,d),W_p)$ be the $p$-Wasserstein space on $(X,d)$. For which $p$ and $(X,d)$ is $(\mathcal{P}_p(...
Carlos_Petterson's user avatar
3 votes
1 answer
403 views

Regularity of transport map

Let $\mu$ and $\nu$ be probability measures on $\mathbb{R}^n$ with first moment and suppose that both $\mu$ and $\nu$ have a densities with respect to the $n$-dimensional Lebesgue measure. Fix some ...
ABIM's user avatar
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2 votes
1 answer
175 views

How to prove the limit of minimizing sequence of measures is again absolutely continuous(w.r.t. Lebesgue) in the minimizing movement scheme?

I am considering the minimizing movement scheme related to the gradient of entropy functional in 2-Wasserstein space. The problem is to minimize the following functional for each fixed $\eta$ which is ...
MikeG's user avatar
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6 votes
1 answer
2k views

Gradient of Wasserstein distance in the sense of Otto's calculus

I am learning the idea of "gradient" of a functional in Otto's calculus. It is defined as follows. Suppose the space we are thinking about is $(\mathcal{P}_{2,AC}(\mathbb{R}^d),W_2)$, the ...
MikeG's user avatar
  • 715
0 votes
1 answer
379 views

Uniqueness of maximizer of dual Kantorovich problem with quadratic(or any strictly convex) cost

I am considering the optimal transport problem under the setting $X=\mathbb{R}^n$, $\mu,\nu\in\mathcal{P}(X)$ be two probability measures, and the cost function is $c(x,y)=|x-y|^2$. We know from ...
MikeG's user avatar
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3 votes
1 answer
529 views

Wasserstein-type concentration inequalities for empirical measures on polish spaces

Let $(\mathcal{X},d)$ be a Polish (metric) space and let $\{X_n\}_{n=1}^{\infty}$ be a sequence of i.i.d. $\mathcal{X}$-valued random elements defined on a common complete (standard) probability space ...
ABIM's user avatar
  • 5,405
0 votes
2 answers
201 views

Couplings as generalized functions

I've been casually reading about optimal transport, and I was intrigued by the Wasserstein metric, in which we define the distance between two measures $\mu$ and $\nu$ on a metric space $X$ by $$ W_p(\...
Danny Stoll's user avatar
3 votes
2 answers
295 views

Wasserstein convergence of "series expansion'' of probability measure

Let $X$ be a Polish space and let $(\mu_i)_{i=1}^{\infty}$ be a sequence of probability measures in the Wasserstein space $\mathcal{P}(X)$ on $X$. Let $(\beta_i)_{i=1}^{\infty}$ be a summable ...
ABIM's user avatar
  • 5,405
4 votes
0 answers
117 views

Improving log-Sobolev inequalities via quadratic regularisation

Suppose that $\mu(dx) = \exp(-\psi(x)) \, \mathrm{dx}$ is a probability measure on $\mathbf{R}^d$. For suitable functions $g \geqslant 0$, define $$\text{Ent}(g) = \int \mu(dx) g(x) \log \left( \frac{...
πr8's user avatar
  • 801
3 votes
1 answer
310 views

Open problem 1.28: $W^{1,1}$ regularity for optimal transport map

While I don't work on the regularity theory for the optimal transport map, I was curious about the open problem 1.28 listed in Ambrosio and Gigli's User's guide: the problem to determine whether we ...
Silentmovie's user avatar
2 votes
1 answer
304 views

An approximation problem w.r.t marginal distribution of coordinates of uniform random vector on high-dimensional unit-sphere

Let $X=(X_1,\ldots,X_d)$ be uniformly distributed on the sphere of radius $\sqrt{d}$ in $\mathbb R^d$. Fix a "sufficiently integrable" function $h:\mathbb R \to \mathbb R$, and define ...
dohmatob's user avatar
  • 6,853
0 votes
0 answers
95 views

Empirical estimation of Brenier map from data

Let $f:\mathbb R^d \to \mathbb R$ be a "nice" (say, continuous) function define $A = A_f := \{x \in \mathbb R^d \mid f(x) \ge 0\}$ and $B =B_f:= \{x \in \mathbb R^d \mid f(x) \le 0\}$, and ...
dohmatob's user avatar
  • 6,853
0 votes
2 answers
534 views

Wasserstein distance between $N(0,1/d)$ and the marginal distribution of $x_1$ when $x=(x_1,\ldots,x_d)$ is uniform on the unit-sphere in $R^d$

Let $x=(x_1,\ldots,x_d)$ be uniformly distributed on the unit-sphere in $\mathbb R^d$. Question. What is a good upper-bound for Wasserstein distance between $N(0,1/d)$ and the marginal distribution ...
dohmatob's user avatar
  • 6,853
1 vote
1 answer
100 views

$L^p$-barycenters via continuous selectors

Let $\mathbb{P}$ be a Borel probability measure on $\mathbb{R}^n$ with $\int_{x \in \mathbb{R}^n} \|x\|^p\mathbb{P}(dx)<\infty$. For which $p\in [1,\infty)$ (other than $p=2$) is the following ...
ABIM's user avatar
  • 5,405
6 votes
2 answers
2k views

Textbooks or lecture notes about mean field games

I am looking for a good introductory level textbook (or lecture notes) on mean field games that would be suitable for a graduate course. Ideally, it would include some brief words about optimal ...
Anita Poller's user avatar
8 votes
1 answer
2k views

What is the intuition behind the Kantorovich potential in optimal transport?

From what I currently understand, under certain conditions one may turn the usual Kantorovich problem - a minimisation problem in terms of measures into a maximisation problem in terms of functions. ...
Nate River's user avatar
  • 6,313
0 votes
0 answers
291 views

Convexity of a set of probability densities

Consider the space of probability densities $(P(\mathbb{R}^d), W_2)$ (probability measures on $\mathbb{R}^d$ with 2-Wasserstein distance). How can we determine if a subset $Q$ is convex? I know that a ...
900edges's user avatar
  • 153
0 votes
1 answer
275 views

Upper bound on the $p$-Wasserstein distance $\mathcal{W}_p(\xi,a\,\xi)$ for some constant $a \neq 0$

Let $\xi$ be a random vector taking values in $\mathbb{R}^d$. Is there an upper bound on the $p$-Wasserstein distance $\mathcal{W}_p(\xi,a\,\xi)$ for some constant $a \neq 0$? I have seen that if $p=...
Juan Miguel Morales González's user avatar
1 vote
0 answers
130 views

Orthogonality in Wasserstein tangent space for discrete measures with equal mass

Let say I have $N$ discrete probability measures $(\mu_1,...,\mu_N)$ where each of them has $n$ points in $\mathbb{R}^2$ of equal mass. Let $P(\mathcal{X})$ be the space of these probability measures ...
Jean Hugue's user avatar
2 votes
1 answer
114 views

Reweighting probability measures by convex potentials, and contraction in transport distance

Let $W: \mathbf{R}^d \to \mathbf{R}$ be a convex function such that $\int \exp(-W) = 1$, and define probability measures $\mu_y$ by $$\mu_y (dx) = \exp( - W (x - y)) \,dx,$$ i.e. each $\mu_y$ is a ...
πr8's user avatar
  • 801
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
1 vote
0 answers
85 views

Producing a minimiser for the Kantorovich problem from a minimiser of the Beckmann flow problem

Notation: We denote by $\mathcal M$ the set of vector valued measures on $\mathbb R^d$ whose divergence is a scalar measure (in the weak sense). Definitions: Consider the Beckmann flow minimisation ...
Nate River's user avatar
  • 6,313
4 votes
1 answer
396 views

Is the optimal transport of radially symmetric measures also radially symmetric?

Let $\mu$ and $\nu$ be radially symmetric probability measures on $\mathbb R^d$. Consider the Kantorovich optimal transport problem between $\mu$ and $\nu$, with convex, nonnegative cost. Suppose ...
Nate River's user avatar
  • 6,313
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
3 votes
0 answers
82 views

Semiconcavity estimate for the squared distance on a compact Riemannian manifold

I am currently reading this paper on the Riemannian structure of the Wasserstein space over a compact Riemannian manifold (my question doesn't concern the Wasserstein metric), specifically Section 4.1,...
grogTheFrog's user avatar
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
8 votes
0 answers
1k views

Wasserstein distance and Monge-Kantorovich-Rubinstein duality

The definition of Wasserstein $p$-distance between two measures $\mu$ and $\nu$ on a Polish space $X$ is given by $$ W_p(\mu, \nu)^p = \inf_{\gamma \in \Pi(\mu, \nu)} \int_{X \times X} d(x, y)^p\; d\...
SMS's user avatar
  • 1,407
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
1 vote
1 answer
261 views

Parameterization of exponential family

Let $\{\mathbb{P}_{\theta}\}_{\theta}$ be an exponential family of probability measures, all with finite mean. Under what conditions is the parameterization map $\theta\mapsto \mathbb{P}_{\theta}$ ...
ABIM's user avatar
  • 5,405
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
113 views

Statistical analysis of optimization solution involving Brenier potentials?

I'm reading the paper https://arxiv.org/pdf/1905.10812.pdf where strongly convex approximations to Brenier potentials are approximated. Let $\mathcal{E}$ be a partition of $\mathbb{R}^{d}$ and $ 0\leq ...
Kashif's user avatar
  • 383
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
0 votes
0 answers
72 views

Optimal transport mapping between sets with a common subset

What would the optimal transport mapping between two sets with a common subset be? The problem I'm thinking about is the following: I'm in $\mathbb{C}^n$ and I have two distributions $\mu$ and $\nu$ ...
Kashif's user avatar
  • 383
0 votes
1 answer
84 views

One question about how to get $\inf_{\nu\in\mathcal{M}(Z)} \sum_{j=0}^N F_j^*(\nu)=-(\sum_{j=0}^N F_j^*)^*(0)$?

In this paper: Matching for teams by G. Carlier and I. Ekeland (2010), https://www.jstor.org/stable/25619994?seq=1#metadata_info_tab_contents: they claim that follows a standard argument in Ekeland ...
Hermi's user avatar
  • 288
5 votes
0 answers
140 views

What kinds of gradient-flows on $\mathbb R^d$ preserve the log-concavity of the distribution $\mu_0$ of starting point $x_0$

Let $\mu_0$ be a log-concave distribution on $\mathbb R^d$ and let $f:\mathbb R^d \to \mathbb R$ be $C^2$. Let $x_0$ be sampled uniformly at random from a log-concave distribution $\mu_0$, meaning ...
dohmatob's user avatar
  • 6,853
0 votes
2 answers
275 views

The uniqueness of Barycenters in the Wasserstein space

I am reading the paper Barycenters in the Wasserstein space by Martial Agueh and Guillaume Carlier. In Proposition 3.5, they prove the existence and uniqueness of $$\nu \mapsto \sum_{i=1}^p \frac{\...
Hermi's user avatar
  • 288
2 votes
0 answers
101 views

$CD(K,N)$ condition for non complete metric measure spaces

That's basically it. I would like to know if it's possible to define the ${\sf CD}(K,N)$ condition for metric measure spaces that are not necessarily complete. The references I have found on this ...
Mauricio Che's user avatar
2 votes
1 answer
767 views

Integer solution of optimal transport

Let us consider two vectors $\mathbf{a}=(a_1,...,a_n)$ and $\mathbf{b}=(b_1,...,b_m)$ so that each quantity is an integer $a_i,b_j \in \mathbb{N}$. It represents for example supply and demand. Let $\...
Titouan Vayer's user avatar