Comments (12)
CMA-ES isn't related to NEAT, but you get to know the optimizer infrastructure.
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CNE also does the same as CMAES for point 1. Are there any drawbacks to initializing the population by adding matrices generated by arma::randn() to the starting point?
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Right, no need to restrict the starting point.
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@zoq For point 2, besides your suggestions, could we also include the initial step size as a parameter? Currently, we experience a problem when we use larger bounds, since the initial step size becomes too large. This causes the CMAES implementation to fail tests when the parameters are changed to include larger bounds (For e.g., [-25,25] for the LogisticRegressionTest). This problem is fixed if we change the step size.
Moreover, I think instead of using one set of bounds for all parameters of a candidate, the user should be able to apply constraints to each parameter separately, since that is more practically useful. Please let me know your thoughts on this
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Sounds reasonable to me, I think this is already included in #88?
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No, I wanted to make sure it was alright before including it. I'll make the required changes to #88 soon
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Sounds good, thanks!
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Do you want me to wait to release the next version of ensmallen until #88 is merged?
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I'm not sure whether that question was meant for me, but I should let you know that i might not be able to work on #88 much for the next couple weeks, since I'm going to be busy with exams and stuff.
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No worries, we can just get #90 merged and then release, assuming that that one is basically ready (I think it is, I'll try and review it tomorrow).
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Sure :)
Also, about applying box constraints for each parameter, i don't think we currently have any implementation that does that yet. Would it be fine to add a parameter in the constructor for an arma::cube
where each slice has the constraints? Or is there some other way you would like to do this?
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Personally I don't see any issue with an arma::cube
for constraints. It might be worth having that as a separate constructor, so that the user can choose to provide two double
parameters for the minimum and maximum in each dimension (which is easy to make a hypercube with), or a more complex arma::cube
.
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Related Issues (20)
- Compiling errors ensmallen 02.18.02 using VS2019 armadillo.lib 10.08.02 and mlpack.lib 03.04.02 HOT 6
- The example to use the constrained function HOT 4
- AugLagrangian with constraints validation HOT 8
- Multi-objective functions both MOEA/D-DE and NSGA2 - Examples using SchafferFunctionN1 HOT 1
- Implementing Function Type for Partial Derivatives HOT 3
- Does ensmallen work with armadillo >=10.0? HOT 5
- Enable HTTPS on ensmallen.org HOT 1
- Debian build (test) failure on i386 HOT 7
- ProgressBar() does not work with L_BFGS HOT 3
- Bounds for search space HOT 5
- During AugLagrangian's optimization, L_BFGS sets coordinates to nan HOT 6
- Migrate from Catch v2 to v3 HOT 3
- Using optimizer with integers HOT 6
- Custom early stop callback HOT 12
- SCD isn't stochastic and perhaps should be called CD? HOT 2
- 2.20 documentation + link issues
- Which optimizer should I use? HOT 2
- [PowerPC] Bus error during running tests: `KERN_PROTECTION_FAILURE at address: 0x00000000` HOT 7
- [aarch64] One test failure in Johnson844LovaszThetaFMatSDP HOT 8
- benchmarking framework for single-objective evolutionary optimization algorithms HOT 1
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