-
most of the optimization based problem
```python
# f(report)
job.optimize(f, CMAES()).submit().report()
```
this should cover most of the optimization problem we have on pulses
-
# Non-gradient
- [x] Differential evolution: done #9
- [ ] DRAM: @ben18785 ? Very old PR #35
- [x] DREAM: done #10
- [x] Emcee hammer: done #12
- [x] Haario AC: done #6
- [x] Haario-Bardenet AC…
-
Hello and thanks, that is a wonderful library.
I would like to improve with cmaes the optimization time over bruteforce start/step/stop-scheme.
I work a lot with different types and bounds of val…
-
How to solve the problem?
parser.add_argument('--num_trials', type=int, default=32, help='evaluate average reward over X trials')
parser.add_argument('--num_threads', type=int, default…
-
感谢分享SamCon的代码,对我有很大帮助。看到demo里面还有improved samcon的演示,效果看起来更好,请问后续会分享improved samcon的代码吗,感谢~
-
https://www.cs.toronto.edu/~duvenaud/papers/blackbox.pdf
https://www.disneyresearch.com/project/boxelization/
https://www.lri.fr/~hansen/cmaes_inmatlab.html
-
**Description:**
I am experiencing an issue with the `problem.make_net` method. When I try to generate a trained network using the `center` parameter from the `searcher.status`, the method fails un…
Duxo updated
2 months ago
-
Hi,
I am a neophyte in deep learning. I am trying to use sferes2 with map_elites module. I successfully configure and build sphers2. I use check command. I got the following result.
**\* No errors d…
-
Modular CMA is packaged and should be easy to integrate in Nevergrad.
Example of usage of "modcma" below:
import random
import numpy as np
from modcma import AskTellCMAES
DIMENSION = 10
…
-
Hello,
I use CMAES and its C implementation to deal with stress inversion.
When my problem is very ill conditionned, I have a floating point exception in cmaes.c at line 893/894
```c
/* cumulat…