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The struct `MOIOptimizationNLPEvaluator` does not support `lag_h`, and instead uses the much less efficient `cons_h`, ref
- https://github.com/SciML/OptimizationBase.jl/issues/91
This makes constr…
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# 🚀 Feature Request
A complete t-batch support (especially t-batch acquisition optimization) for parallel optimization with different experimental setups, if this is a good idea.
## Motivation
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"Loop peeling" is a compiler optimization that unrolls a loop into two copies. In the variant of interest here, the first copy executes the first iteration of the loop, and the second copy executes th…
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### Operating System
- [ ] Windows
- [ ] macOS
- [ ] Linux
- [ ] FreeBSD
- [ ] OpenBSD
- [ ] Android
- [ ] iOS
- [ ] Nintendo Switch
- [ ] PlayStation 5
- [ ] Xbox
- [ ] Web Browsers
### What featur…
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**Motivation**
* Faster than raw operations by 200-1000x (Lazy optimization, Rust, Fastest Algorithms for every simple operation)
* Big amount of supported features
* Less memory intensive
* Can…
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**Reported by jorn.baayen on 9 Mar 2016 15:57 UTC**
Currently, FMI 2.0 ME supports first order directional derivatives. This is useful for gradient-based optimization and parameter estimation.
Y…
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### What type of enhancement is this?
Performance, User experience
### What subsystems and features will be improved?
Query planner
### What does the enhancement do?
I think this is a r…
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History commands:
2343 git clone https://github.com/llSourcell/Second_Order_Optimization_Newtons_Method.git
2344 cd Second_Order_Optimization_Newtons_Method/
2347 sudo easy_install pip
2348…
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There is already support for BilinearOperator in `pyproximal/pyproximal/utils/bilinear.py` and the PALM optimizer; however,
they do not scale to second-order methods such as Levenberg-Marquardt (LM) …
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- Made sure you’re on the latest version => feature/lrc
- Used the search feature to ensure that the bug hasn’t…