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Eigenvalue problem with quadratic constraints

$\circ$ Consider the following eigenvalue problem : $$Ax=\lambda x \hspace{0.5cm} (1)$$ where matrice $A \in \mathbb{R}_{n \times n}$ is a positive semi-definite with eigenvectors $x = (x_{1},x_{2},.....
user41037's user avatar
2 votes
2 answers
798 views

Survey on Compared Running Time: Ellipsoid Method vs. Simplex Method

If you look through papers on the Ellipsoid Method, there is a large agreement, that the Ellipsoid Method, although theoretically polynomial, is in practice way slower than the Simplex Method. ...
Skrodde's user avatar
  • 329
35 votes
4 answers
5k views

Why are optimization problems often called "programs"?

Why are optimization problems often called programs? linear programming geometric programming convex programming Integer programming ...
ziggystar's user avatar
  • 461
4 votes
2 answers
2k views

Simplified knapsack problem

There is a problem that I can not solve. Given a set of items (each item has some integer weight) we have to fill bag with some number of copies of these items, with the only restriction that the ...
Leo-guest's user avatar
0 votes
1 answer
85 views

About the suboptimality of linear estimators

Let $X$ be a random variable and $N$ a Gaussian noise independent from $X$. We observe $Y=X+N$ and want to estimate $X$ based on $Y$ to minimize the mean square error $mmse(X|Y):=E(\hat X(Y)-X)^2$. ...
EEStudent's user avatar
5 votes
0 answers
194 views

A linear optimization problem on a graph

Let $G=(V,E)$ be a finite graph and let $f$ be any positive function defined on the vertices. Put weights on the vertices $v_{i}$, way $w_{i}$ so that $\sum_{i=1}^{n}w_{i}\leq 1$. Assume that every ...
TOM's user avatar
  • 2,288
3 votes
1 answer
1k views

For interior point methods of linear programming, what is the "L" in the computational complexity $\mathcal{O}(n^3 L)$?

My question is about interior point methods of linear programming. Suppose the constraint matrix $A$ has $m$ rows and $n$ columns, and $m<n$. The state-of-the-art methods, like primal dual interior ...
RandomStuff's user avatar
1 vote
0 answers
196 views

Interior point optimisation using big M for L1 norm on linear system using Dikin's Affine method

I am a 4th year undergrad surveying student studying computations, specifically $L_{1}$ norm minimisation of residuals in large data sets. To start with (and probably to finish with) I'm using a set ...
lsdavies's user avatar
  • 111
7 votes
2 answers
1k views

Is a given point in the interior of the convex hull of a given finite collection of points?

Suppose I have the convex hull $P$ of a finite collection of points in $\mathbb{R}^d,$ and I want to see whether a point $p$ is contained in $P.$ This is a standard (some would say the standard linear ...
Igor Rivin's user avatar
  • 96.4k
0 votes
1 answer
2k views

eigen-decomposition solution? is it unique?

Assume an N*N covariance matrix (Q) which is a positive definite matrix. The decoder X is assumed to be N*s, where s<=N. X is calculated to be s eigenvectors corresponding to s minimum eigenvalues. ...
asd2014's user avatar
2 votes
1 answer
1k views

Finding integer points inside of a parallelogram

Suppose $P = \{p_1,\ldots,p_4\} \in \mathbb{R}^2$ defines a quadrilateral (here, specifically, a parallelogram). In the particular case I'm dealing with, I know that there exists at least one point ...
Eric Tressler's user avatar
1 vote
0 answers
256 views

Equal maximum and minimum in a large-scale linear programming

For a linear optimization of an integral (with integral constraints), I perform a linear programming for the equivalent series. Maximum and minimum of the LP problem tend to be equal as I increase the ...
Amir Kazemi's user avatar
2 votes
0 answers
39 views

In what paper was the shrinkage parameter introduced to the nelder-mead simplex direct search algorithm?

I have read lots of papers referencing a 4th shrinkage parameter when talking about the Nelder Mead Simplex method. However, I cannot see any shrinkage parameter in the flow chart of the original ...
Craig's user avatar
  • 21
2 votes
0 answers
163 views

existence of lattice point in polytope

This question was probably asked before but here goes. I have a convex polytope given by $Ax\leq b$ for a specific integer matrix $A$ and integer vector $b$. I need a simple method/result on how to ...
Alex's user avatar
  • 501
2 votes
1 answer
689 views

Why does the LP Formulation of the MST Problem need Topology Constraints?

I am looking for an example that demonstrates the necessity of either subtour-elimination or of connectivity constraints in the LP formulation of the MST In the internet I only could find the LP ...
Manfred Weis's user avatar
  • 13.2k
0 votes
2 answers
244 views

Rewrite optimization objective

Hi, I wanted to ask, under which conditions can one rewrite the optimization objective $\min_x f(x)\;\;\;s.t.\;\;\;g(x) \leq s$ as $\min_x g(x)\;\;\;s.t.\;\;\;f(x) \leq t$ I have particular ...
rodms's user avatar
  • 409
1 vote
2 answers
306 views

Name of operations on two vectors

Suppose we have two vectors $x\in \mathbb{R}^n$ and $y\in \mathbb{R}^m$. I could define the mapping $$ T: \mathbb{R}^n\times \mathbb{R}^m \rightarrow \mathbb{R}^{n\times m} $$ as follows $$ T(x,y) = ( ...
Fedor Nikitin's user avatar
0 votes
2 answers
340 views

positive semidefiniteness: a psd matrix substracted by another rank 1 psd matrix

Given that $A$ is a positive semidefinite matrix, $x$ is a vector, $\lambda_0 \in [0, +\infty) $ is a real non-negative number. I want to know the answer to the following optimization problem. $$ \...
Shaohua's user avatar
  • 101
2 votes
2 answers
129 views

LP constraint enconding

I have an objective function to be maximized $obj(x) = \sum_i \gamma_i x_i$ with $x_i \in \mathbb{R}$ With multiple constraints of the form: $\min_{y \in 0,1} (\sum_{i \in A} \alpha_i x_i + \sum_{i ...
Gecko's user avatar
  • 21
1 vote
1 answer
296 views

Deducing Linear Inequalities

Let $X_1,X_2,\ldots,X_n $ be indeterminates. Denote by $S$ the set of all linear inequalities of the form $X_{i_1}+X_{i_2}+\ldots+X_{i_k} \geq k,$ with $k \in \{ 1,2,\ldots,n \}$ and $1 \leq i_1< ...
user21277's user avatar
  • 185
2 votes
1 answer
227 views

Arrangements of hyperplanes

Fix $n>0$ and $X\subseteq\mathbb{R}^n$. A function $f:X\longrightarrow\mathbb{R}$ is linear if it is of the form $$ f(\bar{x})=a_1x_1+\ldots+a_nx_n+b $$ for some $a_i,b\in\mathbb{R}$. Suppose we ...
Gabe Conant's user avatar
  • 3,274
1 vote
1 answer
4k views

What does "Vertex Solution" mean?

Hello! I come across the word "vertex solution" in the context " We can also assume that x and y are vertex solutions,so that the sequence {x,y} remains in a finite set." Could anybody know any ...
tendow's user avatar
  • 13
0 votes
0 answers
104 views

Big eigenvalues of a special stochastic matrix

Given a matrix $M$ of size $n\times n,$ we write its different eigenvalues by $x_1,x_2,\ldots,x_m$ with $m\leq n$ such that $|x_1|>|x_2|>|x_3|>\cdots|x_m|,$ and call $x_2\doteq |\lambda_2|(M)....
Umberto's user avatar
  • 105
9 votes
1 answer
3k views

Inverse of a totally unimodular matrix

A unimodular matrix $M$ is a square integer matrix having determinant $+1$ or $−1$. A totally unimodular matrix (TU matrix) is a matrix for which every square non-singular submatrix is unimodular. A ...
qianchi 's user avatar
5 votes
1 answer
3k views

Maximizing supermodular functions

I have a real supermodular objective function which I want to maximize with constraint. The constraint is on the size, like |A|=k . I am wondering if anyone can give me more information about a ...
Majid Yazdani's user avatar
2 votes
0 answers
63 views

Put positive polynomial in finite intersection of half-spaces

This is a cross-posting of a MSE question (which did not attract any attention there so far). Denote by $V={\mathcal P}_{n,d}$ the space of polynomials in $n$ variables with degree at most $d$, ...
Ewan Delanoy's user avatar
2 votes
1 answer
130 views

Fastest 'Oracle' Algorithm for satisfying a single linear constraint on a convex set?

In this paper by Arora, Hazan, and Kale (http://www.cs.princeton.edu/~arora/pubs/MWsurvey.pdf) a method is given for using the Multiplicative Weights Update algorithm to quickly solve Linear Programs ...
Sam Stern's user avatar
  • 121
2 votes
3 answers
752 views

Reference Request for Integer factorization with LP/ILP

Have there been attempts to factor integers with Linear Programming? Searching the internet suggests that for Integer Factorization only Number Theoretic algorithms, like sieves, are taken into ...
Manfred Weis's user avatar
  • 13.2k
2 votes
1 answer
2k views

Finding a point farthest away from $k$ points in a polygon

There are $k$ points placed inside a polygon and I am interested in finding a point inside the polygon (not necessarily on its boundary) who's minimum distance to any of the $k$ points is maximized. ...
marc's user avatar
  • 57
1 vote
2 answers
1k views

Efficient algorithm finding 'a' solution of system of linear inequalities

I'm working on rational number field $\mathbb{Q}$. Is there an efficient algorithm finding a solution of system of linear inequalities? In many computer algebra systems like Sage or Maple, there ...
Moon's user avatar
  • 627
3 votes
2 answers
791 views

complexity of finding optimal matchings of given fixed size

It is known, that maximal matchings (i.e. matchings with the maximal number of edges) and optimal matchings (i.e. matchings for which the sum of edge weights is optimal) can be calculated in ...
Manfred Weis's user avatar
  • 13.2k
1 vote
0 answers
1k views

Robust optimization in matlab using fmincon [closed]

I am trying to implement the following optimization (from this paper) in Matlab using fmincon: $\min_\omega\omega'\Sigma\omega$ subject to $\min_Ur_p \geq r_0$ where $\Sigma$ is a positive definite ...
Geraldine Bailey's user avatar
0 votes
1 answer
2k views

Find edge weights that fit given node weights

Let $G = (V,E)$ be a connected simple graph (unweighted, undirected, no selfloops) on $n$ nodes. Let $\mathbf{d} := (d_1, d_2, ..., d_n) \in \mathbb{R}_{>0}^n$ be a vector of arbitrary given node ...
cubic lettuce's user avatar
3 votes
1 answer
4k views

Schur complement and negative definite matrices

Hello, My question regards to the Schur complement lemma. Consider the matrix $M=\left( \begin{array}{cc} A & B\\\ B^T & C \end{array}\right) $. According to the lemma $M\geq0$ iff $C>0$ ...
AD1984's user avatar
  • 155
19 votes
2 answers
2k views

Is the tensor product of polyhedra a polyhedron?

Conventions: A polytope in a finite-dimensional $\mathbb R$-vector space $V$ is defined to be a convex hull of finitely many points in $V$. A polyhedron in a finite-dimensional $\mathbb R$-vector ...
darij grinberg's user avatar
1 vote
0 answers
126 views

Matrix Minimax problem

I have the equation $\Sigma_k(M_k{p_k})V=EV$, where the $M_k$ are n*n real Hermitian matrices, $V$ is a n*n eigenvector matrix, $E$ a dim-n energy eigenvector and the $p_k$ scalar parameters. The $M_k$...
Hauke Reddmann's user avatar
4 votes
1 answer
585 views

How to implement linear constraints that include several absolute values

Dear all, I am trying to implement a linear constraint that includes several absolute values in the form: Abs(A) + Abs(B) + Abs(C) + Abs(D) + ... = 1 Since the minimization problem includes quite a ...
Hugo's user avatar
  • 41
0 votes
1 answer
2k views

Finding linearly independent columns of a large sparse rectangular matrix

I have a problem that necessitates solving a large non-negative least-squares problem. My matrix A is large, sparse, highly rectangular (num rows >> num cols) and nearly binary. However, A is not ...
Rob's user avatar
  • 103
5 votes
2 answers
2k views

Bounding the minimal maximum norm of a solution of a linear system.

I would be grateful for pointing me out a reference to some general bound on the $\ell_{\infty}$ norm of a solution of a linear system. To be specific, suppose that we have an underdetermined linear ...
user3645's user avatar
  • 191
5 votes
2 answers
888 views

relation between solution of a linear program and its perturbation

I have a linear program over a finite set of points $(x_1, x_2,\ldots, x_m)\in\mathbb{R}^n$: $$ \max_j c' x_j $$ Suppose the solution of this LP is obtained at a point $x_{j_1}$, which is a vertex ...
Abhishek Kumar's user avatar
1 vote
2 answers
1k views

Nonstandard Hessian approximations in Gauss-Newton

The Gauss-Newton algorithm optimizes functions $$ E(x) = \sum f(x)^2 $$ by approximating f as (locally) linear, in which case the Hessian of $E$ is approximated as $$ H = 2 \sum {J_f}^T J_f $$ Now ...
Alex Flint's user avatar
1 vote
2 answers
444 views

Levenberg-Marquadt near the minima for non-zero-residual problems

I'm using the LM algorithm to do gradient descent in a model fitting context. I'm minimizing: $$ c(x) = \sum ( f_i(x) - y_i )^2 $$ I'm noticing that after a few steps when I'm close to the minima, I ...
Alex Flint's user avatar
2 votes
1 answer
126 views

Is it possible to represent non-linear ranking type constraints as equivalent linear constraints?

I have formulated a linear program with binary indicator variables $z_i(a)$ which is equal to $1$ if the $i^{th}$ document is of rank $a$ and $0$ otherwise. The other variables in the linear program,...
stressed_geek's user avatar
0 votes
0 answers
103 views

Gauss-Newton for quotient functions

I'm optimizing a function of the form $$ \sum \frac{ \|\mathbf{f_i}(x)\|^2 }{ g_i(x)^2 + h_i(x)^2 } $$ where $x$ is a real vector, $\mathbf{f}(x)$ is a real vector, and $g(x)$ is a scalar. My first ...
Alex Flint's user avatar
1 vote
1 answer
769 views

Results for minimizing the norm w.r.t a unitary matrix

Suppose $x \in \mathbb{R}^n$, $B,U \in \mathbb{R}^n\times\mathbb{R}^n$ and $U$ a unitary matrix. Define $g_{U}(x) = || BUx||$ where $||.||$ is some norm or norm-ish function on $\mathbb{R}^n$ (not ...
safetyduck's user avatar
0 votes
0 answers
194 views

A linear program related question

Dear all, recently, I encountered the following problem. It is closely related to the order of growth for UMD constants of all $n$-dimensional Banach lattice. Let $\alpha^k \in (\alpha_1^k, \alpha_2^...
Yanqi QIU's user avatar
  • 769
0 votes
0 answers
79 views

Computing maximum point for minimal function of a family of linear functions

Let $x \in S^n $ where $S^n = ${$ [x_1,x_2,...,x_{n+1}]\in \mathbb{R}^{n+1} \mid x \ge 0 , \sum x_i = 1 $} and let $f_i : I^n \to \mathbb{R}$ be a finite $m$-sized family of LINEAR functions such that:...
PolvoAzul's user avatar
0 votes
1 answer
130 views

Cascading minimization problems

Hi all. Suppose I have a linear programming problem on the vector variable $x$ that has many solutions and let $U$ be the set of these solutions. Suppose I have a second LP problem on $y \in U$. ...
ashade's user avatar
  • 57
3 votes
2 answers
10k views

linear programming with OR restrictions

Hi all. I have a linear program with the restriction that every variable can be zero or greater than or equal to a positive constant. That is: minimize: $w^Tx$ subject to: $Ax=b$, $Cx \le d$ and for ...
ashade's user avatar
  • 57
0 votes
2 answers
891 views

Find both maximum and minimum values in linear programming problem

Hi all. I have a linear programming problem where I need to find both maximum and minimum values of the objective function. The optimal points are not relevant. Is there an efficient way to do so?
ashade's user avatar
  • 57

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