Linked Questions

81 votes
6 answers

Optimization when Cost Function Slow to Evaluate

Gradient descent and many other methods are useful for finding local minima in cost functions. They can be efficient when the cost function can be evaluated quickly at each point, whether numerically ...
Jared Becksfort's user avatar
1 vote
2 answers

Response Surface Methodology (RSM) for A Mathematical Model

I would like to create a second order polynomial model using Response Surface Methodology (RSM) for a non-polynomial mathematical model. For example, I would like to represent $f(x)=x_1 + \sin(x_1x_2) ...
arvindrajan92's user avatar
3 votes
2 answers

Function Approximation vs. Regression

Some background before I state the questions: I have a $d$-dimensional random vector $X=(X_1,\ldots,X_n)$ and a function $f:\mathbb{R}^d\rightarrow\mathbb{R}$. Ultimately my goal is to understand $f$ ...
g g's user avatar
  • 2,688
1 vote
1 answer

How to use Design of Experiment (DoE) to reduce the number of simulations?

I am planning to do simulation for parametric study and there are 9 parameters in total. I was suggested to use DoE to reduce the number of simulations that I need to do. I studied the basic of DoE ...
the terrible's user avatar
1 vote
1 answer

Select optimal points for Gaussian process with a well-known target function

I'm currently trying to select the optimal points for a Gaussian Process Regression, and the important thing is that i already know the whole target function. Therefore, it's not Online Learning ...
Tbertin's user avatar
  • 399
1 vote
1 answer

How do I choose which design of experiments method to use?

I'm setting up a computer simulation (which I know changes the design of experiments methods) and I can't really determine how to choose which design of experiments (DOE) method to use. I'm a little ...
tpg2114's user avatar
  • 367
2 votes
1 answer

Why are global search algorithms not used in DoE?

I'm reading about Design of Experiments via various textbooks (e.g. Montgomery's), and powerful global optimization methods (such as Ant Colony Optimization) are not used. They rely only on a basic ...
questioner50's user avatar
1 vote
0 answers

Space filling vs D,A,I,etc-optimal experiment design [closed]

What are some of the criteria for choosing one family over the other of experiment design methods ? How does this choice relate to the model of the response ? I left factorial / fractional factorial ...
cladelpino's user avatar
1 vote
1 answer

Sampling plan for surrogate modelling

I am trying to develop a surrogate model for a thermoacoustic engine. The engine is modelled in a program called DeltaEC. I have developed automation code so that I can change parameters, run the ...
Francis's user avatar
  • 13
0 votes
0 answers

Is there a good framework for using Active Learning (reinforcement learning?) for Experimental Design?

We have a frequent problem that we deal with in a research environment that essentially boils down to finding the optimum conditions in a certain experimental space. At the moment we essentially solve ...
dsbbsd9's user avatar
1 vote
1 answer

DoE for optimization / control approach?

I'm wondering whether a DoE approach could somehow be used as kind of an optimization algorithm? One of my current tasks is to find a set of five parameter which max a sixth one (see here for more: ...
Ben's user avatar
  • 3,473
0 votes
0 answers

Choose factors that best represent the entire space

(I'm brand-new here. I have strong mathematical and computing backgrounds, but little knowledge of statistics. If this question belongs elsewhere, I would appreciate a pointer to where.) I believe ...
Scott Sauyet's user avatar