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Questions tagged [global-optimization]

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I'm solving an inverse PDE problem by fitting a signed distance function (SDF) to a 2D shape using polynomial approximation (Chebyshev basis). The loss consists of: a boundary loss: $ u = 0 $ on the ...
Roua Rouatbi's user avatar
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Let $A$ be a non-singular matrix in $\mathbb{R}^{n \times n}$. Let $S^{n-1}$ denote the surface of the unit $n$-sphere in $\mathbb{R}^{n}$. Suppose we know that there exists an $x \in S^{n-1}$ such ...
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Let $f: \mathbb{R}^{n} \rightarrow \mathbb{R}_{+}$ be a non-negative and differentiable convex function which vanishes in a non-empty convex set $\Omega$ - possibly unbounded. Usually, when one ...
R. W. Prado's user avatar
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Given a dataset $X,$ having $p$ features, organize the units $x_i \in X $ into fixed number of clusters $g,$ with fixed cluster size $B.$ Clustering policy: minimize the sum of a linear combination of ...
BiasedBayes's user avatar
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Suppose we have difficult peak fitting problems where the the users wish to fit asymmetric peaks to their experimental data by the least squares method. One such function is illustrated below: Here $...
ACR's user avatar
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We know there is a necessary condition for the non-negativity of multivariate polynomials in the paper "Sum of Squares Decompositions of Polynomials over their Gradient Ideals with Rational ...
Werther's user avatar
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Let $A, B$ be Banach spaces, and for any $a\in A$, $B_a\in B$ is a measurable subset. Consider the following optimization problem: $$L(a)=\inf_{b\in B_a}\ell(b),$$ where $\ell(b)$ is a infinite-times ...
Jeff 's user avatar
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Let $n$ be any integer greater than $2^{10^6}$. Given any $s\le (\log_2 n)/1000$ integers $1=q_1\le q_2\le \cdots q_{s-1}\le q_s=n$. Prove that $$\min_\ell\left(\sum_{i=1}^\ell q_i\right)\left(\sum_{i=...
Nader Bshouty's user avatar
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This is an unconstrained convex optimization problem. Let $\mathcal{N}=\left\{1,\ldots,n\right\}$, $2\leq n<\infty$. Suppose there are many strongly convex functions $f_i(x)$, where $x\in\mathbb{R}^...
lzzz's user avatar
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Let $f$ be some given well-behaved function. Consider the following optimization problem overall probability distribution on $[0,1]$ \begin{align} \max_{P_X : X\in [0,1] } \left| \frac{\mathbb{E} [ ...
Boby's user avatar
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Let $\Omega$ be an open bounded subset of $\mathbb{R}^2$ and $f\in L^2(\Omega)$ be a given function. Consider the optimization problem $$\mathrm{min} \int_\Omega u(x) f(x) \,dx\,,$$ where a minimum is ...
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I have the following optimization problem with cubic constraints, which is hard to solve. Are there any ideas, or related references, of solving such a problem? $$ \begin{array}{ll} \underset {y, z} {\...
Erik's user avatar
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Let $\{\Omega_{j}\}_{j\in\mathbb{N}}$ be a sequence of smooth bounded domains in $\mathbb{C}^{n}$ such that $\Omega_{j}$ converges to a smooth bounded domain $\Omega$ in the sense that the defining ...
Naruto's user avatar
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I am looking for an algorithm to solve the following optimization problem $$\max_{\mathbf{w}}\sum_i\text{sign}(\mathbf{w}^T \mathbf{x}_i)$$ where $\mathbf{w}$ and each $\mathbf{x}_i\in\mathbb{R}^d$. ...
user3750444's user avatar
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I have asked this question on math.stackexchange.com but even though I gave a bounty, I was not able to receive any answers at all, so I'm posting it here again, hoping that the question is not too ...
alhal's user avatar
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Let $G=(V,E)$ be a connected network with $|V|=n$. Consider the following optimization problem I'm trying to know under which conditions the following minimization problem has solution : $${\sum _{i=1}...
Goga's user avatar
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Suppose we have $N$ lines in general position (any two lines, but no three lines, meet at a point) ($N\geq 3$). Let the smallest bounded region have area $1$. Determine the minimum (or possibly ...
Lieutenant Zipp's user avatar
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For $n\geq 4$, let $V_n$ be the maximum volume of the convex hull of $n$ points on the unit sphere (in $\mathbb{R}^3$, although information on higher dimensions is welcome as well). I'm sure the ...
Gro-Tsen's user avatar
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I am trying to come up with a generalisation of the Kelly formula for optimal fractional betting but and have hit a roadblock. The Kelly criterion is usually explained via a game that ends in 1 of 2 ...
lotuspaperboy's user avatar
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Let $\Phi$ be the Gaussian CDF and for $\gamma\ge 0$ and $h>0$, define a loss function $\ell_h:\{\pm 1\} \times \mathbb R$ by $$ \ell_{\gamma,h}(y,y') := \phi_{\gamma,h}(yy') := \Phi((yy'-\gamma)/h)...
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I am looking for some problems in which we know the value of optimal solution and should find just a vector of variables. For example in N-Queens problem we know the value of optimal solution (that is ...
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I am working on a problem and for that purpose, I need to prove the following inequality. Let $t\in [0,1]$ and set $$ z_0=1-4t(1-t)\sin^2(4x)\\ z_1=1-4z_0(1-z_0)\sin^2(3x) $$ I need to show that for ...
MO B's user avatar
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I want to optimize the following function: $$ argmin_{x} f(x) = g(x) + h(x) $$ , where I can get $\nabla_xg(x)$, but cannot calculate $\nabla_xh(x)$. The derivative-free method, such as the Hill ...
Koukyosyumei's user avatar
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Let $n\geq2$. Is it true that the minimax problem: $$ \min_{p\in\mathcal{P}}\max_{H\in\mathcal H}p^tH\bar{p}, $$ where $\mathcal H\subset\mathcal{M}(n)$ is a strictly convex bounded subset of ...
user111's user avatar
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How do I find two orthonormal 4D vectors, $(x_0,x_1,x_2,x_3)$ and $(y_0,y_1,y_2,y_3)$, which maximize this function: $-19x_1y_0 - 33x_2y_0 + 11x_3y_0 + 19x_0y_1 - 21x_2y_1 - 33x_3y_1 + 33x_0y_2 + ...
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Theorem: Suppose ${\bf g} :\mathbb{R}^n \mapsto \mathbb{R}^n$ is continuously differentiable, there exists a set $\mathcal{A} \subset \mathbb{R}^n$ such that $\bf g$ is uniformly Lipschitz on $\...
RLip2's user avatar
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2 answers
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Under some reasonable assumptions integrals with large exponents can often be computed via saddle point approximations, e.g. $$\int e^{-\lambda f(x)}\approx e^{-\lambda f(x_0)},\qquad \lambda\to\infty$...
Weather Report's user avatar
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1 answer
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In this question, a non-random version of "almost supermartingale" theorem is proved. Here, I would like to extend/apply the non-random version to the slightly different situation. I wonder ...
user550103's user avatar
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842 views

Suppose we have a function $f(x,y,z)$ where the inputs are uniform from 0 to 1. The output is either $+1$ or $-1$. And there is a partial symmetry $f(x,y,z) = f(z,y,x)$. Tell me what the minimum of ...
Kunal Marwaha's user avatar
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Perhaps stupid question. Question: Can "almost supermartingale" theorem be equally applicable to prove the convergence of some algorithms solving non-random optimization problems? Attempt ...
user550103's user avatar
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As we all know, a classic optimization problem can be represented in the following way: Given a function $f: A \to \mathbb{R}$, find an element $x_0 \in A$ such that $f(x_0) \le f(x)$ for all $x \in ...
Shaun Han's user avatar
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I know that a constrained linear optimization problem can be transformed into an unconstrained binary quadratic optimization problem (UBQP). Does anyone know if the inverse result is solved in the ...
UnclePetros's user avatar
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As we all know, a classic optimization problem can be represented in the following way: Given: a function $f: A \rightarrow \mathbb{R}$ from some set $A$ to the real numbers Sought: an element $x_0 ∈ ...
Shaun Han's user avatar
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2 votes
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I do not see many works that use global optimization algorithms to solve decentralized control problems. Here the decentralized control problem means some entries of the feedback matrix are ...
fibon's user avatar
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1 vote
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I am curious about the general relation between nested, successive minimization (M1) and asymptotic minimization (M2) as defined in the following. What one wants is to implicitly minimize a sequence ...
Sebastian K.'s user avatar
3 votes
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329 views

Suppose I have a linear optimization problem involving random variables on some (infinite) probability space $\Omega$. For example, need to maximize expectation $E[Q]$ of random variable $Q$ subject ...
Bogdan's user avatar
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1 answer
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(apologies for the n00b question) Let's say we have a vector of length $n$, with to-be-determined values: $a_1, a_2, ...,a_n$. And we have information that partial sums of these elements are equal to ...
Tal Galili's user avatar
1 vote
0 answers
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Given a complex rectangular matrix $A$ $(k \times n)$, I am interested in solving the following optimization problem over $(k\times n)$ complex matrices $x$: $$ \mathrm{arg}\max_X \,\mathrm{trace}(X^...
hichem hb's user avatar
  • 387
4 votes
1 answer
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Let $d\in\mathbb N$, $k\in\mathbb N$ and $f:\mathbb R^d\to\mathbb R^k$ be differentiable. Say that $v\in\mathbb R^d$ is a descent direction at $x\in\mathbb R^d$ if ${\rm D}f(x)v<0$ (component-wise) ...
0xbadf00d's user avatar
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1 answer
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Let $Y$ be a nonempty region in $\mathbb{R}^n$. I am designing an algorithm which given a point $x_0$ outside $Y$ in a finite number of steps lead to a point $x_n∈ Y$. The way I do it is that I have a ...
Slava Rychkov's user avatar
5 votes
1 answer
303 views

Let $A\in\mathbb{C}^{m\times n}$, $B\in\mathbb{C}^{n\times k}$, $C\in\mathbb{C}^{k\times m}$ be given complex matrices. The objective of the optimization problem is \begin{equation} \mathop {\arg \min ...
hichem hb's user avatar
  • 387
16 votes
1 answer
618 views

Thomson's problem asks for the minimum-energy configuration for $N$ electrons on a sphere (refs: https://en.wikipedia.org/wiki/Thomson_problem, https://sites.google.com/site/adilmmughal/...
Alex Meiburg's user avatar
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1 vote
1 answer
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Most (stochastic) "gradient descent" type algorithms (such as Nesterov-accelerated gradient-descent or ADAM) seem to be well-defined only for functions which are either: lower semi-...
AB_IM's user avatar
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How to prove the zero slope point is a global maximum in this non-concave program for a function with binomials? I need to find the (global) maximum of the following constrained problem: $$\max_{CAP} \...
Silvester's user avatar
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For a given $q\in (0,1]$, define the $l_q$-ball as $$\mathbb{B}_q(R_q)\mathrel{:=}\left\{\theta\in\mathbb{R}^d\,\middle\vert\,\sum_{j=1}^d \lvert\theta_j\rvert^q\leq R_q \right\}. $$ For a given ...
Hepdrey's user avatar
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2 votes
0 answers
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Context. I'm reading the manuscrip "Nonlinear Error Bounds via a Change of Function" by Dominique Azé and Jean-Noël Corvellec (J Optim Theory Appl 2016), and I'm having a hard time ...
dohmatob's user avatar
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4 votes
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Context. I'm looking for a "natural" definition of subdifferentials on riemannian manifolds. Given a function $F:\mathbb R^m \to \mathbb R$, its Fréchet-subdifferential at a point $w \in \...
dohmatob's user avatar
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Let $L_i:X\rightarrow [0,\infty)$ be continuous (objective) functions defined on a metric space $X$ and suppose that $$ L_1(x)\leq L_2(x)\leq L_3(x)\qquad (\forall x \in X). $$ Here, I imagine that $...
AB_IM's user avatar
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0 answers
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Apologies in advance for being somewhat vague. I'm trying to get pointers to establish a connection between a common trick used in practice in optimization, and the exponential map in differential ...
Athere's user avatar
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3 votes
1 answer
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Let $Y$ be a Banach space and equip $Y$ with the weak topology. Now, let $X$ be a closed, bounded, and convex subset of $Y$ and suppose that the relative (weak) topology on $X$ is metrizable with ...
AB_IM's user avatar
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