All Questions
1,019 questions
2
votes
1
answer
254
views
On the infimal convolution of two norms on $\mathbb R^n$
$\newcommand{\R}{\mathbb R}$For natural $n$, $a\in\R^n$, and real $t>0$, let
\begin{equation*}
K:=K_{n,t}(a):=\inf_{x\in\R^n}(\|a-x\|_2+t\|x\|_1),
\end{equation*}
\begin{equation*}
M:=M_{n,...
- 128k
0
votes
1
answer
88
views
Is the mapping $F(a):= \arg\min_{x \in \mathbb R^n} \|x-a\|_2 + \|x\|_1$ non-expansive?
Fix $a \in \mathbb R^n$ and let $\|\cdot\|$ be any norm on $\mathbb R$ (e.g $\ell_1$ norm). For any $a \in \mathbb R^n$, it is clear that the function $f_a(x) := \|x-a\|_2 + \|x\|$ is strictly convex ...
- 6,853
0
votes
1
answer
110
views
Orthogonal projection of a point centrally-symmetric closed convex subset of $\mathbb R^n$ never expands the coordinates of the point
Let $C$ be a closed convex subset of $\mathbb R^n$ which is symmetric about the standard coordinate axes. For example, think of $C$ as the unit-ball for an $\ell_p$-norm, for some $p \in [1,\infty]$. ...
- 6,853
1
vote
0
answers
24
views
Minimax statistical estimation of proximal transform $\mbox{prox}_g(\theta_0)$, from linear model data $y_i := x_i^\top \theta_0 + \epsilon_i$
tl;dr: My question pertains the subject of minimax estimation theory (mathematical statistics), in the context of linear regression.
Given a vector $\theta_0 \in \mathbb R^d$, consider the linear ...
- 6,853
3
votes
0
answers
174
views
Any reference on Jensen inequality for measurable convex functions on a Hausdorff space?
I asked this question on math.stackexchange and I was suggested that asking it may be more appropriate. This is part of my research which tries to extend some of Choquet's theory to some non-compact ...
- 204
6
votes
2
answers
341
views
For most directions does the supporting hyperplane meeting a bounded convex set meet it in one point?
Let $C\subseteq \mathbb R^n$ be non-empty, convex and compact. For $v\in S^{n-1}$, let $H_v$ be the supporting hyperplane in the direction of $v$ (i.e., $H_v$ is the boundary of the smallest closed ...
- 2,555
2
votes
1
answer
119
views
Analytic value of $\alpha := \sup_{(x,y) \in C} ax+by$, where $C := \{(x,y) \in \mathbb R^2 \mid x^2 + y^2 \le 1,\,x^2 + c y^2 \le R^2\}$
Let $a,b \in \mathbb R$, $R \ge 0$, and $c > 0$. Define $C := \{(x,y) \in \mathbb R^2 \mid x^2 + y^2 \le 1,\,x^2 + c y^2 \le R^2\}$, and set
$$
\alpha := \sup_{(x,y) \in C} ax + b y.
$$
Question. ...
- 6,853
0
votes
1
answer
67
views
Analytic formula for minimizer of $f(x) := \sqrt{(x-a)^\top S(x-a)}+ r \|x\|_2$
Let $S$ be a positive-definite $n \times n$ matrix and define $\|z\|_S := \sqrt{x^\top S x}$ for any $x \in \mathbb R^n$. Let $a$ be a fixed vector in $\mathbb R^n$ and $r \ge 0$, and consider the ...
- 6,853
0
votes
1
answer
539
views
Method for (binary) optimization under constraints
I would like to know if there is a method to solve the Problem.
Problem:
Maximize the following function: $$f(p_{1,i},p_{2,i},\dotsc,p_{m,i})=\sum_{i=1}^{n}\begin{bmatrix}p_{1,i} & p_{2,i} & \...
- 3
20
votes
3
answers
2k
views
Convergence of convex functions
I can prove the following result.
Theorem 1. Let $f_n:\mathbb{R}^n\to \mathbb{R}$ be a sequence of convex functions
that converges almost everywhere to a function $f:\mathbb{R}^n\to\mathbb{R}$.
Then ...
- 28k
3
votes
1
answer
210
views
Probabilistic Taylor theorem for concave functions
This paper proves a probabilistic version of Taylor's theorem
\begin{equation*}
\mathbb{E}g(X) = \sum_{k=0}^{n-1} \frac{g^{(k)}(0)}{k!} \mathbb{E}X^k + \frac{\mathbb{E}X^n}{n!} \mathbb{E} g^{(n)}(X_{(...
- 45
2
votes
0
answers
164
views
Convex ordering of measures that are obtained by different push-forwards of a same measure
Suppose that we have a probability measure $\rho$ which is supported on $\mathbb{R}^d$ and absolutely continuous w.r.t. the Lebesgue measure. Take two vector fields $F, G : \mathbb{R}^d \rightarrow \...
- 21
1
vote
0
answers
59
views
How do I incorporate Ito's lemma into the solution for a finite-horizon stochastic cake-eating problem?
I'm interested in finite-horizon, continuous-time cake-eating problems in which the agent has a time-horizon $W$ over which to eat the cake, and then chooses an optimal consumption path $\{h_t\}_0^W$, ...
- 11
0
votes
0
answers
63
views
Direct (first-order ?) algorithm to minimize $u(x) := \|x-a\|_C + r\|x\|_p$
Fix $a \in \mathbb R^n$, $r \ge 0$, $p \in \{1,2\}$, and a positive-definite matrix $C$ of order $n$. Define $u:\mathbb R^n \to \mathbb R$ by $u(x) := \|x-a\|_C + r\|x\|_p$, where $\|z\|_C := \sqrt{z^\...
- 6,853
0
votes
1
answer
143
views
$\mathrm{ILP}$-formulation for Minimum Maximal Matching (MMM) Problem
Despite some online searching I couldn't find examples of dedicated Integer Linear Programs ($\mathrm{ILP}$s) for determining smallest matchings, that are not contained in a larger one.
It seems that ...
- 13.2k
2
votes
1
answer
121
views
Can we use the solution to two optimisation problems to solve a third, bigger, one?
Background
Say we have an optimization problem $$\min_x f(x) = g(x) + h(x)$$
where $g$ is differentiable and convex, and $h$ are convex but not necessarily differentiable. If $g$ is the mean squared ...
- 33
4
votes
2
answers
610
views
Unit ball of the sum space
Let $V$ be a vector space and $\|\cdot \|_1$ and $\|\cdot\|_2$ two norms on $V$.
Let $\|\cdot\|_+$ be given by
$$ \|v\|_+ := \inf_{v = v_1 + v_2} \|v_1\|_1 + \|v_2\|_2 $$
It is well-known that $\|\...
- 39k
1
vote
1
answer
181
views
Linear programming with "nice" matrices
Consider the following linear programming problem
\begin{array}{ll}
\text{minimize} & \mathrm 1^{\top} \mathrm x\\
\text{subject to} & v\le \mathrm A \mathrm x \le u\\
& \mathrm x \geq ...
- 650
5
votes
3
answers
526
views
How to prove this (corollary of) hyperplane separation theorem?
$X$ is a nonempty convex subset of $\mathbb{R}^n$ whose element is $x=\left(x_1,...,x_n\right)$.
The theorem is as follows.
If for each $x\in X$, there is an $i \in \left\{1,...,n\right\}$ such that $...
- 159
7
votes
2
answers
497
views
Proving the set $\left\lbrace \frac{(x + y)^2}{\sqrt{y}} \leq x - y + 5, y > 0 \right\rbrace$ is convex
I have recently picked up a course on Convex Analysis in my spare time, but feel I'm not quite up to speed with the 'tricks' for proving a set is convex.
I have managed to prove this by moving all ...
2
votes
1
answer
877
views
Interpreting mincost flow dual variables
Consider the task of finding flow of size $b$ with minimum possible cost.
It may be formulated as linear programming in a following way:
$$\boxed{\begin{gather}
\min\limits_{f_{ij} \in \mathbb R} &...
- 1,171
0
votes
2
answers
630
views
Smooth approximation for non differentiable function
Let $f(t) = \min(\frac{1}{\lvert t\rvert}, 1)$. I would like to find a smooth approximating function $g$ such that $f(t) \leq g(t)$ for all real $t$. Is there a nice function $g$ out there? Any ...
- 3,625
0
votes
1
answer
64
views
Round Robin volleyball Tournament [closed]
Consider a set of N teams (N even number) that must make a
Round Robin Tournament. To each pair i; j, i ≠ j, of teams there is associated level
of interest si,j ∈ {1;2;3} of the match between them (1 =...
4
votes
2
answers
252
views
Hausdorff dimension of the non-differentiability set a convex function
Let $X \subset \mathbb R^d$ be open, $f : X \to \mathbb R$ and
$$
E := \{x \in X : f \text{ is not Fréchet differentiable at }x\}.
$$
Then we have the following result which is
Theorem: If $X= \...
- 835
-4
votes
1
answer
98
views
Convex combination of $\frac{1}{x}$ inequality [closed]
Let $0 < x_1 \leq ... \leq x_n$ and $\sum \alpha_i = 1, \alpha_i \geq 0$. Show
$\sum \frac{\alpha_i}{x_i} \leq \frac{x_1 + x_n - \sum \alpha_i x_i}{x_1 x_n} $. Since the left side looks like a ...
2
votes
1
answer
227
views
Solving linear programming without solving linear programming
Let $v_1, \cdots, v_n$ be vectors in $\mathbb R^k$, and let $M$ be the Gram matrix of them.
It's possible to determine from $M$ and $k$ whether the only vector that has nonnegative inner product with ...
- 9,501
3
votes
1
answer
375
views
Derivative of distance function to a convex set in CAT(0) space
Let $(X,d)$ be a complete CAT(0) space. We denote by $T_x X$ the tangent cone at a point $x\in X$ and by $d_x$ its associated distance. So $(T_x X,d_x)$ is also a complete CAT(0) space. In CAT(0) ...
- 91
4
votes
0
answers
481
views
Generalized Jensen's inequality for positively homogeneous functions
The function $f:V \to \hat{\mathbb{R}}$ is said to be positively homogeneous iff $f(\alpha v) = \alpha f(v)$ for every $\alpha \in \mathbb{R}_{++}$. Here $V$ is a real vector space and $\hat{\mathbb{R}...
- 519
2
votes
1
answer
400
views
Convex series and closed convex hulls in normed spaces
Let $(X, \lVert \cdot \rVert)$ be a normed space over $\mathbb{R}$ and $A = \{ a_1,a_2 \ldots \} \subseteq X$ be a closed bounded set.
Let $\overline{\mathrm{co}}(A)$ denote the closed convex hull of ...
- 820
4
votes
1
answer
318
views
Does smoothing a non-log-concave distribution make it more log-concave?
Suppose that $p$ is a density on $\mathbb{R}^d$ that is $C^2$ and nonzero everywhere, and such that the Hessian of its negative logarithm is lower bounded:
$$-\nabla^2 \ln p\succeq L$$
for some matrix ...
- 371
2
votes
1
answer
372
views
Who called Farkas' fundamental theorem a lemma?
Farkas proved his famous result (which, nowadays, is fundamental in optimization theory) in 1902 and called it Grundsatz der einfachen Ungleichung which may be translated as fundamental theorem of ...
- 16.4k
2
votes
0
answers
79
views
Convex optimization over compact sets defined as Aumann set-valued integrals
Let $(X,P)$ be a probability measure space. Let $K$ be a convex compact subset of $\mathbb R^d$ and let $F:X \to 2^{K}$ be a set-valued map. Assume that $F$ is:
closed (i.e $F(x)$ is closed for ...
- 6,853
2
votes
1
answer
132
views
Multivariate inequality of floor function
Define $$f(x,a) := (2x-a)\lfloor\frac{x}{a}\rfloor-a\lfloor\frac{x}{a}\rfloor^2.$$
It seems that $$f(x,a)+f(x,b)\geq 2f(x,c),\forall a,b \in [1,x],a+b=2c.$$
I have written a program that has checked ...
- 31
1
vote
0
answers
47
views
Support functions for subset and superset
I have an ellipse $\mathcal{E} = \{x^TAx = 1\}$, and I have a connected subset of an ellipse $U\subset \mathcal{E}$
For a given $\theta$ let $x_U^*(\theta) = \arg \sup\{\langle x,\theta\rangle, x\in ...
- 215
2
votes
0
answers
60
views
Convex body with prescribed normals (i.e. the Gauss map of the boundary)
Let $\mathbf{S}$ be the unit Euclidean sphere in $\mathbf{R}^n$. I write $u \bullet v$ for the scalar product of two vectors and $A \sim B$ for the set-theoretic difference of sets.
Assume $g : \...
2
votes
0
answers
229
views
Convergence in Hausdorff distance of intersection of closed linear subspaces with a given closed convex set
I've run into the following problem when doing some work with non-commutative metric spaces, which seems like something people may have thought about before but I can't find anything on this problem ...
- 135
1
vote
0
answers
113
views
Maximizing a parametric integral over the unit sphere
I am trying to compute the nonnegative quantity
$$
\underset{y\in\mathbb{S}^{d-1}}{\sup}\int_{0}^{t}(\Vert A(\tau)y\Vert_{1}- \Vert A(\tau)y\Vert_{q})d\tau, \quad 1 < q < \infty
$$
where $\...
- 1,538
1
vote
1
answer
331
views
Finding a special solution in a solution set over F2
Given a solution set of a linear system of the following form
$$
\{ \begin{bmatrix}
x_{1} \\
\vdots \\
x_{n}
\end{bmatrix} = \vec{v_1} * x_1 + \dots + \vec{...
- 51
0
votes
1
answer
396
views
What is the best way to choose initial basis when applying simplex method to an equality form of LP?
Currently I'm trying to write a practically fast LP solver for a sparse instance, which is by simplex method with LU decomposition and eta-matrix update. In the development I realized that I'm not ...
- 1
1
vote
2
answers
270
views
Can we substitute this KKT condition into this optimization problem to reformulate the optimization problem?
Suppose I have the following optimization problem
$$ \min\limits_{\mathbf{x},\mathbf{y}} f(\mathbf{x},\mathbf{y}) \tag{1} $$
It is already known that the target function $f$ is continuous and ...
- 73
4
votes
2
answers
315
views
Connecting $2n$ points in $\mathbb R^2$ with line segments s.t. each point belongs to exactly one line segment
I'm trying to do a certain simulation related to the toric code and I'm looking for an algorithm that connects $2n$ points ($n \in \mathbb Z_+$) in $\mathbb R^2$ with line segments with the following ...
- 269
0
votes
1
answer
320
views
Correct way to conduct equilibrium scaling of linear/integer/MIP program
I would like to scale my linear/integer program and also mixed-integer program using the equilibrium scaling method. I have worked on two research papers and one research book. However, they did the ...
- 21
1
vote
0
answers
61
views
Linear programming robustness to input perturbations
I'm running a linear program whose parametrization depends on the output of a neural network. I was wondering if there exist results on how robust linear programs are towards perturbations in their ...
- 11
3
votes
2
answers
905
views
Is a convex, lower semicontinuous function that is bounded from below, actually continuous?
While thinking about convex functions, I managed to put together the following proof which I find a bit too good to be true. $X$ is a topological vector space that is also a Baire space.
Lemma: Let $f ...
- 651
2
votes
1
answer
644
views
How to maximise infinity norm of $x$ with constraint $Ax \le b$ using linear program? [closed]
I want to maximise the infinity norm of $x$, subject to constraint: $Ax \le b$. I think you can use a linear program to solve this, but how do you go about formulating it?
2
votes
1
answer
197
views
Convex/concave points of a differentiable function
I am wondering about the following question: A strictly convex (concave) differentiable function $f:\mathcal{R}\to\mathcal{R}$ has the geometrical property that its graph lies completely above (below) ...
- 689
0
votes
0
answers
115
views
Explicit equation for border of the Minkowski sum of sets
Assume we have sets of the form
$$
M_j = \{x\in\mathbb{R}^d : f_j(x) \le 0,x \ge 0\}
$$
where $x\ge 0$ means $x_i \ge 0 \quad \forall i=1,\dots, d$.
Goal
I am looking for an (explicit) representation ...
- 385
0
votes
1
answer
101
views
Estimation via projecting onto a convex body
Assume that $\theta$ is in a convex body $K \in \mathbb{R}^n$ and we observe $y = \theta + z$, where $z$ is a noise term (following, say, the normal distribution). Consider an estimator of $\theta$ by ...
- 773
8
votes
1
answer
697
views
Is the square root of the Kullback-Leibler divergence a convex map?
$\newcommand{\KL}{\operatorname{KL}}$Let $X$ be a Polish metric space and $P(X)$ the space of probability measures on $X$. Given $\mu, \nu\in P(X)$, recall that
$$\KL(\mu\parallel\nu) = \begin{cases}\...
- 345
3
votes
1
answer
179
views
On the convexity of certain set of random vectors
Let ${\cal X}$ be the set of pairs of random variables $(X,Y)$ with finite expectations. For constant $c\in[0,1]$, define set
$$
\{(X,Y)\in{\cal X}:\exists a\geq 0, \, b\geq 0 \text{ such that } E[\...
- 7,182