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Tentei paralelizar mas não deu certo, o código não acha posições melhores com a paralelização que foi feita. Não sei o que faltou.
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This is difficult enough to deserve its own issue, since some new parts need to be implemented.
In reference to issue #59 .
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From looking at several implementations of BO, many are running optional solvers in replacement of LBFGS, including:
- CMA-ES: https://pypi.python.org/pypi/cma
- DIRECT: https://pythonhosted.org/DIREC…
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### Package Name/Version
cmaes/0.10.0
### Webpage
https://github.com/CMA-ES/libcmaes
### Source code
https://github.com/CMA-ES/libcmaes
### Description of the library/tool
From the Readme:
l…
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- pyribs version: 0.3.1
- Python version: N/A
- Operating System: N/A
### Description
It seems we may have some errors in the CMA-ES implementation.
For instance, when calculating covar…
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@es-clip hi,
i released a biggan + clip + cma-es notebook in parallel with bigsleep, which to my best knowledge was the first solution combining clip and cma-es, and at the time allowed me to get res…
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Hello, may I bother you, I would like to ask if there are any literature references for the specific theory of your Fast CMA-ES code. If possible, I would like to read the corresponding papers for a d…
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### Motivation
Optuna currently supports only single-objective CMA-ES for sampling, it would be useful to have multi-objective CMA-ES as a lot of tasks need to consider multiple objectives to be op…
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Instead of training the whole model let's optimize only a small randomly selected model part (e.g. 5% of connections) at each optimization step:
```python
class OpenES:
...
def ask(self)…
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### Description
Currently, the CMA-ES implementation doesn't support negative weights. Implement this feature.
Note: some thought is required for filter-based selection.
Reference on active C…