Questions tagged [constraint]
The constraint tag has no usage guidance.
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1answer
51 views
contraints on parameters in MCMC
I run a basic version of mcmc, based on example given in this Metropolis-Hasting tutorial
...
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0answers
11 views
Sample subsets with distribution proportional to elementwise product
I have a set of $n$ elements, $x_1,x_2,\dots,x_n$, each with a weight $w_1, w_2,\dots, w_n$. I want to sample a subset of fixed size $k$ such that the probability of drawing $\{x_a,\dots,x_b\}$ is ...
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2answers
72 views
What are some of the approaches of defining joint pdf under sum constrain?
For example, we have three random variables,
$x_1 = Uniform(10,20)$
$x_2 = Uniform(20,40)$
$x_3 = Uniform(50,150)$
which follows the condition $x_1+x_2+x_3 = 100$
I am looking for a joint ...
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0answers
9 views
Timeseries space consumption optimization for machine learning model
I need to train machine learning model that can run on device with low memory. My features come from aggregations of time-series so I need to store all data in this time-series until it leaves the ...
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0answers
24 views
GMM: can a constrained regression perform better than an unconstrained regression?
I have one linear regression with a set of explanatory variables and an other set of instrument variables.
In my constrained regression, one of the coefficient for a given variable is constrained to ...
1
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2answers
34 views
Normal distributed random variables with constraint?
Consider $n$ random variables $X_i$ with $i=1,2,...,n$, each drawing values from identical normal distributions with mean $\mu=0$ and standard deviation $\sigma=const.$ so that expectation values are $...
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0answers
20 views
Constraints on low dimensional representations of data
Is there literature discussing introduction of constraints to loss functions in order to specify certain structures on low dimensional representations? If so, how do they compare the efficacy of the ...
1
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1answer
17 views
Clustering with constraint on minimum size of cluster
I have dataset of $n$ objects, I want to cluster them according to correlation and I want to divide the dataset into groups of similar objects of sizes not less than 50 - because I use clustering for ...
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0answers
20 views
Accelerated Projected SGD under box constraints
Are there generalizations of ADAM or Adagrad algorithm that allow box constraints for the parameters to be incorporated in the gradient descent step? Is it valid to simply run the algorithm as usual ...
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0answers
17 views
significance in linear regression with constraints
I have a problem which is similar to linear regression, but differs in two main points: 1) the number of regressors is equal to the number of observations and 2) I have constraints on the regressors.
...
0
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1answer
63 views
How do I design this multi-objective fitness function for use with genetic algorithm?
I have a multi-objective optimization problem that I am applying genetic algorithm (GA) to solve. Currently, there are only 2 objectives:
minimize cost
maximize validity
The cost minimization is ...
0
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1answer
28 views
Correlation of Vectors with Constrained Sum
Taking the correlation of vectors with a constrained, fixed sum (say, a simplex, where sum is always 1) will induce spurious negative correlations, since increasing one element always means decreasing ...
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0answers
38 views
Multilabel classification problem where a number of output labels are in certain range
I am tackling a multi-label classification task.
In this problem,
we have 13 classes
For one sample $x \in R^{20}$, $2 \leq |h(x)| \leq4$
Here, $h(x)$ means the prediction labels of sample x by ...
2
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0answers
35 views
Does this distribution family exist?
Let $D$ be a one-parameter distribution family whose support is the positive reals. Let $D_x$ be a distribution from this family parametrized by its mean $x \ge 0$, let $X \sim D_x$ and $Y \sim D_y$ ...
0
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0answers
16 views
Constraints on covariance matrix's correlation, and covariance matrix decomposition. [duplicate]
I have a $3 \times 3$ covariance matrix $\boldsymbol{\Sigma}$.
I have two questions
1) which constraints on the correlations $\rho_{ij}$ must be satisfied to have a positive definite matrix?
2) does ...
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0answers
65 views
How to penalize change of states in Hidden Markov model?
I'm trying to fit a HMM on a sequence of observations and I would like to introduce some constraints that would penalize an excessive number of changes of state in the complete sequence (where "change"...
1
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0answers
26 views
Minimal requirement for reaching a feasible solution in non-convex constrained gradient descent
The problem is as follows:
$\max_x f(x) \enspace , \enspace \text{s.t.} \enspace g(x) \leq \alpha $
We can not assume that either $f$ nor $g$ are convex, on the contrary - we can assume they are ...
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0answers
47 views
Restriction in bayesian likelihood expression
I'm doing MCMC simulation but I'm confused in some part of my model. I dont know which of my likelihood expression is right.
My model is as following.
$\gamma$ = $(\gamma_{1},\cdots,\gamma_{K})$ and ...
0
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2answers
328 views
How to use equalities as constrains with constrOptim in R
I want to solve a matrix system which have several solutions (infinite since it is overdetermined - 6 equations with 8 unknowns). However, the way I want to do it is to a criterion for the variables, ...
2
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2answers
361 views
Coordinate descent with constraints
When performing constrained optimization on a smooth, convex function using coordinate descent, for what types of constraints will the algorithm work ? (i.e. converge or reach an approximate optimum ...
1
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0answers
53 views
2
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1answer
94 views
L2 SVM (squared hinge) theory
The linear L2 SVM can be intuitively understood as
\begin{equation}
\text{minimize } f(\boldsymbol{w}) = \frac{1}{2} \Vert\boldsymbol{w}\Vert^2_2 + C \sum_{i=1}^m \xi_i^2 \tag{1}
\end{equation}
...
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3answers
165 views
Generating identically-distributed random variables with a constraint
Is there a way to generate identically-distributed random variables (eg $x_1,x_2,x_3,x_4$) with the following constraint:
$\frac{x_1*x_2}{x_3*x_4} ≡ 1$
$x \in (0,1)$
Please note that simply ...
2
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0answers
66 views
Eigenvalue-constrained covariance estimation and AIC
I'm estimating a covariance matrix $\Sigma$ from datasets where the number of dimensions $p$ may be close to or larger than the number of data points. To obtain a well-conditioned estimate, I use the ...
0
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0answers
135 views
Maximizing profit, using GAMS?
I've been given the following optimization problem and this is what I have done so far:
Cuppa Coffee Company mixes specialty coffee blends to sell to SmartBux, a small
chain of coffee shops. The ...
0
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1answer
38 views
How to compute a non linear mix model with links between the parameters and their variance in R?
I'm working on a biological problem where we want to modelize the impact of a treatment and a chemical modification on the measured quantity of a molecule (peptides).
We will note $x_{ijk}$ the ...
1
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0answers
34 views
Constrained classification - how to classify a set of related items
I need to classify a set of elements into a few categories.
Example:
...
0
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1answer
49 views
Primal constrained (not on $\xi_i$, but on $\mathbf{w}$!) formulation of L2 SVM
I recently came across a statement that the unconstrained primal L2-regularized SVM formulation
$$
\min_\mathbf{w} \lambda \|\mathbf{w}\|^2_2 + \sum_i \max (0, \; 1 - y_i \mathbf{w}^T\mathbf{x}_i)
$$
...
0
votes
1answer
149 views
Monotonic constraints in regression model with interaction
I'm trying to figure out what constraints I need to use to have monotonicity (both on $x$ and $z$) on the regression model with interaction. My model is:
$$\mathbb{E}[Y|x,z]= \beta_0+\beta_1x+\...
0
votes
1answer
103 views
R: Genetic Algorithm supporting dynamic constraints
Is there any package available or some other approach to implement constraints like (x1 < x2) or even more complex relationships provided by some function.
Another desired option would be a ...
1
vote
1answer
485 views
Reinforcement learning (Q-learning) under constraint
I want know how to add a constraint to Q-learning. I have an action resulting in two rewards every time (reward 1= delivery cost , reward 2= delivery time). I want to minimize the cost while ensuring ...
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0answers
284 views
How can I impose such constraints on regression coefficients in practice?
I am estimating a linear regression model with the dependent variable $y$ and $k$ explanatory variables $x_1, \ldots, x_k$:
$$y=\beta_0+x_1\beta_1+ \ldots+ x_k\beta_k + \epsilon.$$
In the estimation ...
1
vote
1answer
114 views
Fitting a regression with constraints on the relationship between one independent variable and the dependent variable?
Let's say I have a dependent variable y (a rating of the pleasantness of shopping at a particular store from 0 to 100), and 10 independent variables ...
1
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1answer
41 views
Stan - find dimensions of an object - lower and upper question [closed]
I have a bunch of objects (roughly rectangular) , for some of which I know what their dimesions - x, y, and ...
2
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0answers
81 views
Constraints on the moments of a bounded probability distribution
Consider a probability distribution with support on $[0,1]$. Suppose the first $n$ raw moments $m_1,...,m_n$ are given. What are the constraints on the $(n+1)^\text{th}$ moment? Obviously we have the ...
4
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0answers
34 views
Algorithm that preserves the order of the predicted variable
Hi all,
I need some advice on possible algorithms that I can apply to the following problem (if possible with pointers to implementations of these algorithms).
The dataset:
I have some dataset ...
1
vote
2answers
448 views
Is there a clustering algorithm that can take a maximum distance from any mean as a constraint?
I am building an analytical tool that depends on being able to take a bunch of 1 dimensional numbers and group them into categories based on how close each number is to the mean of the group. However, ...
1
vote
1answer
77 views
Zero restrictions in state-space models/ Kalman Filter
I am estimating a state space model using Kalman and the EM algorithm in Matlab, using Kevin Murphy's toolbox (http://www.cs.ubc.ca/~murphyk/Software/Kalman/kalman.html). My question should in ...
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0answers
22 views
Clustering with Parametric distance in terms of error
I want to solve a constraint-based clustering problem. The constraint is a function of the points in one cluster. In simpler terms, I want to divide the data points into two clusters (A and B), such ...
0
votes
1answer
178 views
Two-way ANOVA with modified sum-to-zero constraint
I have a dataset with two categorical predictors and a continuous response. Suppose the predictors have $a$ and $b$ levels, respectively, with group-specific parameters $\alpha_1, \dots, \alpha_a$ and ...
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0answers
216 views
Understanding constraints in regression / maximum likelihood
There are many questions about implementing parameter constraints. My question is about understanding constraints. What follows is a very contrived example that I thought up on the spot. Feel free to ...
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0answers
62 views
What are some of the methods for constrained maximization?
This question is related to a question that I asked earlier. Since I am not able to decipher the algorithm in the original question, I would like to know whether there are other algorithms that can ...
1
vote
1answer
68 views
How can I add minimum and maximum constraints to a coefficient in a regression in R?
I have an array ($Y$) with a series of data to which I must fit the sum of some other arrays $(X_1,X_2,X_3)$. The expression is:
$Y = c_1*X_1 + c_2*X_2 + c_3*X_3 + e$
I need to add some constraints (...
1
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0answers
26 views
Constrain multiple Regression for symmetric Stiffness
I want to do a 3-degree polynomial regression like
$$y_i=a_0+\sum_{u=1}^{k} a_{u}x_{i,u}+\sum_{1\leq u \leq v \leq k} a_{u,v} x_{i,u}x_{i,v}+\sum_{1\leq u \leq v\leq w \leq k}a_{u,v,w}x_{i,u}x_{i,v}...
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0answers
35 views
Proposal distribution on a pair of ordered continous parameters
I'd like to sample a pair of continuous parameters which has the constraint that one has to be smaller than the other one. I understand one approach is by rejection sampling by rejecting the samples ...
3
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1answer
1k views
Fit logistic regression with linear constraints on coefficients in R
This is (I think) a routine question, but I haven't seen an answer here. In the past I had to fit logistic regression models with linear constraints on the coefficients, in the case when some of the ...
2
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1answer
2k views
Covariance matrix decomposition and coregionalization
The original question (that can be seen at the bottom of this post) was replaced by this first edit (below)
EDIT I
I give more details about my problem.
First of all let suppose to have K vectors $\...
1
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2answers
85 views
normalization constraint in support vector machine
A support vector machine initially poses the following optimization problem:
$$max_{\gamma, w, b} \gamma \\
s.t\ \\
y^{(i)}(w^Tx^{(i)} + b) \ge \gamma,\ \ i=1,\dots,m \\
||w|| = 1$$
I understand the ...
3
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0answers
2k views
scipy optimization - 'Singular matrix C in LSQ subproblem' [closed]
I'm trying to do a fairly simple optimization, but I keep getting the error 'Singular matrix C in LSQ subproblem'. I've tried to search the internet, however I couldn't find anything about why this ...
3
votes
1answer
160 views
Regression with “proportionality constraints” on unknown parameters
Consider the following model:
$${\bf y} = {\bf X}{\bf b} + {\bf e}$$
where ${\bf y}, {\bf n}\in {\cal R}^m$, ${\bf b}\in{\cal R}^n$, and ${\bf X}\in{\cal R}^{m \times n}$ where $m>n = {\rm rank}(...
