# Questions tagged [least-squares]

The least-squares tag has no usage guidance.

39
questions

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### Weighted Least squares with Multiple Unknowns and Iterations

I am currently working on a problem involving the minimization of the $\chi^2$ deviation between a model matrix ($C_\text{model}$) and a measured matrix ($C_\text{measured}$). by finding the best-fit ...

1
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0
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33
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### Least square with Frobenius norm regularization

$$
\begin{align} f_i &= \operatorname*{argmin}_f \| Af - d \| ^2_{l2} + λ \| P_X(f) - L_r(P_X(f_{i-1})) \|_F^2 \\[8pt] &=M_4^{-1}(A^Hd+\lambda P_X^*(L_r(P_X(f_{i-1})))) \end{align}
$$
where
$$
...

0
votes

1
answer

136
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### Symmetric linear least-squares solution ${\bf X} {\bf A} = {\bf B}$

Given the wide matrices ${\bf A} \in {\Bbb R}^{n \times m}$ and ${\bf B} \in {\Bbb R}^{p \times m} $, where $m > n > p$, form an overdetermined linear system in ${\bf X} \in {\Bbb R}^{p \times n}...

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1
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61
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### Least square error problem ill conditioning

I am trying to understand why I am getting an almost singular matrix in a problem I have.
The problem is a simple as
$$
\min_{X \in \mathbb{R}^{m,n}} \left\lVert AX - B \right\rVert_F^2
$$
Obvioulsy ...

1
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1
answer

164
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### Shape, shift and scaling retrieval of a sampled function

Let $f(x)$ be some unknown continuous square-integrable function defined on the interval $[0,1]$.
Suppose we have $i=1,...,n$ samples $f_i$ of $f$ of the following form:
$$f_i(x)=a_i*f(x+b_i)+c_i$$
...

0
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1
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96
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### Trigonometry/spherical angles/minimum-least-squares [closed]

An issue from 3D tessellated geometry: Find the direction vector of a plane that minimizes the silhouette of a set of triangles. To say it another way, find the direction vector that is most ...

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52
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### Least squares regression with nonnegative error

I'm looking for algorithms to solve a special quadratic programming problem, but I don't know its name or related keywords. Can anyone give me some clues? The problem reads
\begin{equation}
{\min}_x \...

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3
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245
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### How to optimize for the best fit nonuniform-scale-rotation to a given 3×3 matrix?

Given a matrix $L\in \mathbb{R}^{3 \times 3}$, I'm looking for a method to find the closest (in a least squares sense) product of a non-uniform scaling matrix and a rotation matrix:
$$
\min_{s\in\...

4
votes

1
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158
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### Least squares problem with left and right unknowns

For $i=1,...,n$, let $b_i$ be a scalar and $A_i$ be an $k\times l$ matrix. Is there a closed form solution for the following problem assuming $n>k+l$?
$$\min_{x\in \mathbb{R}^k ,y\in \mathbb{R}^l} \...

2
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51
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### Under what conditions is the least-squares approximation bounded with the same Lipschitz gradient constants?

Let $f(x):\mathbb{R}^K\Longrightarrow \mathbb{R}^L$ denote a multivariate continuously differentiable function. All the partial derivatives of $f$ (all its Jacobian elements) are bounded from above ...

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142
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### Solution that minimizes the sum of squared errors, with quadratic constraints

Given symmetric and positive definite $n \times n$ (real) matrices $A_1, \dots, A_m$ and $b_1, \dots, b_m \in {\Bbb R}^{n}$, I am trying to find the solution with the least sum of squared errors of ...

2
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0
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121
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### Given normal equations with nonnegative solution, is there always a subsystem with nonnegative solution?

Given a system of normal equations $A^TAx=A^Tb$ where $A^TA$ is $n\times n$,
what I call the $i$th subsystem is the linear system of size $n-1\times n-1$ where the $i$th column of $A$ has been removed....

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0
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25
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### Minimum eigenvalue of normal matrix with polynomial basis

For each $n\in \mathbb{N}\cup\{0\}$, let $x_n(t)=\frac{t^n}{n!}$ for all $t\in [0,1]$. As the functions $X_N=(x_0 ,\ldots, x_N)$ are linearly independent, the matrix
$
\int_0^1 X_N(t)^\top X_N(t)\,\...

20
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4
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3k
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### Is the pseudoinverse the same as least squares with regularization?

Given a linear system $Ax=b$, the pseudoinverse of $A$ is found as the matrix $A^+$ such that $x=A^+ b$ where $x$ solves the least squares problem $\min \| Ax - b \|^2 $ and $x \perp \mathcal{N}(A)$. ...

3
votes

1
answer

272
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### Concentration inequality for norm of solution to nonlinear least-squares problem

Define the piecewise-linear function $\psi(t):=\max(t,0)$ for all $t \in \mathbb R$.
Let $d,n,k \to \infty$ at the same rate (i.e $n \asymp k \asymp d$).
Let $y_1,\ldots,y_n \in \{-1,1\}$ uniformly ...

1
vote

2
answers

168
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### Robust estimation of $Ax=b$

Problem setting :
$ \underset{x}{\text{min}} \|Ax-b\|$, where $A \in \mathcal{R}^{m \times n}, m\gg n $, full rank.
L1 loss is used for robust estimation using IRLS. The corresponding equation to ...

1
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1
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142
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### Understanding the Time Delay of Arrival trilateration algorithm

I'm trying to algorithmically solve the Time Delay of Arrival problem as part of some mathematics research. The problem is as follows:
Given the location of three receivers in a plane (A, B, and C), ...

2
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2
answers

97
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### Non-parametric regression and curvature

Given a finite set of points $(x_1, y_1), (x_2, y_2), \ldots, (x_n, y_n)$ in the plane, Linear Regression tells us how to find the straight line "$y=a+bx$" best approximating the given points, in the ...

1
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3
answers

84
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### RKHS/non-parametric regression with missing response values

I am interested in doing RKHS regression with missing response variables.
Given input-output pairs $(x_i,y_i)$, I want to estimate a function $f(\cdot)$ as follows
\begin{equation}f(x)\approx u(x)=\...

2
votes

1
answer

300
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### Minimise $\sum_i \begin{Vmatrix}\boldsymbol{x}_i \\ \boldsymbol{y}_i\end{Vmatrix}$

Consider column vectors $\boldsymbol{z}_i$, $\quad i=1,\dots,n$.
Each $\boldsymbol{z}_i$ has $j$ elements and can be expressed as $\boldsymbol{z}_i = \begin{bmatrix} \boldsymbol{x}_i \\ \boldsymbol{y}...

5
votes

2
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778
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### Symmetric linear least-squares solution

Given tall matrices $A$ and $Y$ and the following overdetermined linear system in square matrix $X$
$$AX=Y$$
is there an explicit formula for the least-squares solution if $X$ is constrained to be ...

0
votes

1
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767
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### How to determine the damping factor in Levenberg-Marquardt?

From the algorithm, we can see that it tries different damping factor until it gets a good one by the error. Is the damping factor related to the eigenvalues of the Hessian matrix?

2
votes

0
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30
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### Difference Between Total Least Squares Plane and Plane Orthogonal to Principal Axis of Inertia Tensor

Given a finite set $P$ of points in $\mathbb{E}^3$ , one can calculate an approximating plane either as the solution of a Total Least Squares problem or by interpreting the problem physically, ...

1
vote

1
answer

112
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### Minimization Proof of Conditioning on Gaussian is Gaussian

It is well known that $E[X|X+Y]$ is Gaussian if both $X$ and $Y$ are, and the result can be derived using standard density arguments. However, how can one prove it by only resulting to optimization ...

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128
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### Choice of residual function for least squares error minimization

Good morning,
I have the a set of data $(\sigma,D,\alpha_0)_i$, $i=1...n$ data.
I want to determine two parameters $K_{IC}$, $C_f$ in the basic equation given as
$K_{IC} = \sigma \sqrt{D} k_0(\...

2
votes

2
answers

235
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### In practice, what's the fastest method to find a least square solution rather than using SVD decompostion?

I'm working on a real-time implementation of Lucas-Kanade for optical flow. However, the SVD decomposition to do achieve the least square method to reduce the error seems to take too much time.
A ...

8
votes

3
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326
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### Regularized linear vs. RKHS-regression

I'm studying the difference between regularization in RKHS regression and linear regression, but I have a hard time grasping the crucial difference between the two.
Given input-output pairs $(x_i,y_i)...

5
votes

1
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268
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### Rank-constrained least-squares solution of the Sylvester matrix equation

For the Sylvester matrix equation $AX+XB=C$, I want to find the least-squares solution $X$ via
$$\begin{array}{ll} \text{minimize} & \| AX + XB - C \|_{\text{F}}^2\\ \text{subject to} & \mbox{...

4
votes

1
answer

347
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### Least square solution to $AXB+CXD=E$

I am trying to find the least-squares solution $X$ of the following matrix equation
$$AXB+CXD=E$$
Of course, I know that this equation can be written in the form
$$(B^T \otimes A+D^T \otimes C) \...

3
votes

2
answers

356
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### Standard solution to semidefinite program [closed]

I have an optimization problem of the following form
$$\text{minimize} \,\|Qa-b\|_2 \quad \text{ subject to } Q \succeq 0$$
where $a,b \in \mathbb{R}^n$ are given and the $n \times n$ square matrix ...

2
votes

1
answer

178
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### Reconstruct matrix given all differences of neighbors

We have an unknown $m\times n$ matrix $X=(x_{ij})_{i=1,j=1}^{m,n}$. Assume we are given measurements of the differences
$$x_{i,j+1}-x_{i,j}$$
and
$$x_{i+1,j}-x_{i,j}$$ for all $(i,j)\in \{1,\...

8
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1
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18k
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### Gauss-Newton vs gradient descent vs Levenberg-Marquadt for least squared method

I need to clarify some idea I have in my mind about linear and non-linear regressions. Whatever I know about this topic comes from the book of Taylor "Introduction to error analysis": a set ...

0
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0
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74
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### Why is ideal wavelet selection a least-squares estimate?

In their classic paper "Ideal spatial adaptation by wavelet shrinkage" (http://biomet.oxfordjournals.org/content/81/3/425.short?rss=1&ssource=mfr), Donoho and Johnstone make the following ...

1
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1
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126
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### MSE of measurable function is still conditional expectation

Motivation
Then the usual stochastic filtering problem says that:
$$
\operatorname{argmin}_{Z \in L^2(\mathscr{G}_t)}\,\mathbb{E}[(Y_t-Z_t)^2],
$$
where $\mathscr{G}_t$ is the $\sigma$-algebra ...

1
vote

1
answer

196
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### Least squares problem with constrained solution [closed]

If $a_{m\times 1}$ and $Q_{m\times n}$ ($m<n $) are known, and we know every element of $b$ is between $[-1\ \ 1]$, how to determine $b$ to minimize $\|a+Qb\|_2$?

2
votes

1
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342
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### How to force least squares solution matrix to be diagonal? [closed]

I have the following matrix equation
$$AX=B$$
given $8 \times 3$ matrices $A$ and $B$. $X$ is a $3 \times 3$ diagonal matrix whose main diagonal contains the $3$ unknowns.
Whenever I solve for $X$ ...

7
votes

1
answer

201
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### Least-squares solution of systems of Sylvester equations

The Sylvester equation $AX+XB=C$ has been studied quite a lot and there are known algorithms for solving it.
But has the situation where (an over-determined) system of equations $A_{i}X+XB_{i}=C_{i}$ ...

0
votes

2
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282
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### Solving sparse linear least squares or a positive definite 5-band matrix system fast

I want to quickly solve the following linear least-squares problem
$$\min_{x \in \mathbb{R}^n} \left\| A x - b \right\|_2^2$$
with a special sparse structure where each row in $A$ has only up to $4$ ...

3
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1
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3k
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### How do I optimize over (or take derivative wrt) a square diagonal matrix?

I would like to solve the following optimization problem in $k$-vector $w_i$
$$ \min_{w_i} \quad \left\|P_i - X \mbox{diag} (w_i) Y^T \right\|_F^2 $$
where $P_i$ is a $6 \times 6$ matrix, $X$ and $Y$ ...