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Questions tagged [optimization]

Use this tag for any use of optimization within statistics.

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Minimize variance of sum of weights in clusters

Let us assume we have $n$ products, with $w$ weight for each. Group $n$ products in $k$ bags such that the weights of the bags have least variance. Let there be $h$ bags. Let $h^{th}$ bag contain ...
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glmer model - allFit function

I am conflicted over the results of the allFit() for my glmer model, but this has happened with lmer as well. What do you normally do when all the optimizers, except one, give you a very similar ...
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If $\ell_0$ regularization can be done via the proximal operator, why are people still using LASSO?

I have just learned that a general framework in constrained optimization is called "proximal gradient optimization". It is interesting that the $\ell_0$ "norm" is also associated with a proximal ...
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Density estimation as an optimization problem

Density estimation is the estimation of a probability density function from observed data. Can some of the common approaches to density estimation, such as kernel density estimation, be formulated as ...
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Bayesian update vs optimization in multivariate case

Say I have a multivariate normal vector $r$~$N(\mu , \Sigma )$ and I observe that $y \equiv Pr + \epsilon = Q$ where $P$ is a matrix and $Q$ a vector and $\epsilon$~$N(0 , \Omega )$. Now I ...
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Particle Swarm Optimisation Explained

Is anyone able to provide an intuitive explanation of how particle swarm optimisation works? For example how to minimise a function f(x,y,z). Also, does particle swarm optimisation work for multi-...
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Quadratic programming and interpretation of dual solution (Lagrangian)

Note: this question is about a common data science problem, but I am solving it using a specific piece of software. I believe the problem is common enough that these principles will be common across ...
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Similar loss, different results

I have trained multiple CNNs for image classification. I suspect there is something wrong with my training pipeline, since many of my experiments get very similar training loss at the end of training, ...
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Is there an algorithm for finding the 10 best combinations from a list of 50 parts? [closed]

I've been thinking about a problem that seems pretty generic but I can't seem to find a solution for.. I have a list of 50 values. I need to make 10 groups which are as uniform as possible with ...
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How to enforce smoothness in guided image filtering techniques ? Any preferable model?

Which one (or more) of these three minimization models is the appropriate way to enforce smoothness in guided filtering framework ? \begin{eqnarray} %\begin{aligned} & \sum\limits_{q \in {N}(p)} {\...
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Measure-agnostic learning?

I am studying metrics for evaluation of various learners in a multilabel classification setting. There seem to be more than 10 various measures, leaving me in some kind of doubt which metric to select,...
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Policy optimisation of a neural network which itself depends on the policy

I have a problem I've been thinking about recently and I am just completely stuck with regards to thinking of an appropriate way to tackle it. The set-up is similar to the typical reinforcement ...
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Setting bound constraints in L-BFGS?

How does one choose the bounding constraints for the parameters in L-BFGS? Should these be viewed as a hyperparameter to be chosen subject to a criteria or do they arise as constraints in the typical "...
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Optimal value for multiple input

I run an experiment in which every second I record values of area, circularity, and elongation (there will be probably more variables in the future). I want to find in which second there are the ...
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Gradient on subset of training data is proportional to the true gradient?

I have been thinking of proving the following: Prove that the gradient calculated on a random subset of a training set on average is proportional to the true gradient. However, proving is not my ...
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Fitting flexible spline using ODEs

I'm fitting a series of ordinary differential equations (describing movement through disease states: susceptible, infected, recovered) to weekly counts of a disease through time. I'm solving the ODEs ...
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How to create a variance-covariance matrix for forecasted fantasy basketball scores?

I have three basketball players who have played in games together and I want to find a Variance-Covariance matrix that will be as accurate as possible for their fantasy points in an upcoming game. My ...
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Genetic Algorithms for Feature Selection

Is anyone able to provide a simple explanation of how genetic algorithms can be used for feature selection in machine learning?
31 views

How can we conclude that an optimization algorithm is better than another one for a problem at hand

When we test a new optimization algorithm for a particular problem at hand, what the process that we need to do?For example, do we need to run the algorithm several times, and pick a best performance,...