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## 🚀 Feature
Conjugate gradient descent, and Linear operator as implemented in scipy needs to have a place in pytorch for faster gpu calculations.
## Motivation
Conjugate gradient Descent a…
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Hi,
Are there any implementations where the scaled conjugate gradient (: SCG) method is used to optimize the model's hyperparameters, instead of LBFGS or the stochastic gradient descent?
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Hello!
First of all, thank you for your great work, I am using your library a lot and it's very efficient in removing background!
My issue is that recently I started getting this error after pro…
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Sometimes some is the test cab fail due to numerical issues. In most case (like 98%) they run just fine.
e.g.:
```
mltool $ ./scripts/test_runner.py
mltool-0.1.0.0: test (suite: mltool-test)…
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The request for using the conjugate gradient (CG) method for minimization was raised recently. Here is what I posted at FOCUS repository about my limited experience of using CG. You can have a look an…
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### 🚀 The feature, motivation and pitch
The nonlinear conjugate gradient (CG) method is a good alternative to the L-BFGS optimizer. Features of nonlinear CG:
1. It theoretically converges faster…
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- [ ] SGD
- [ ] Brent's Algorithm in One Dimension
- [x] Generating Set Search (compass search/pattern search)
- [ ] CMA-ES
- [ ] Conjugate Gradient Descent
- [x] BFGS
- [x] Linear Programming
…
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As we discovered when looking at the L-BFGS optimiser (#1083 ) line search algorithms are not that straightforward and are an integral part of Quasi-Newton and conjugate gradient methods. Furthermore,…
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In the comment of `class RidgeSketch`, "ridgesketch" is listed as an option, but in fact it is not implemented.
```python
solver (str): defaults to 'auto'.
If dimensions small, uses direct so…
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The conjugate gradient descent algorithm in scipy is slow and prevents the calling function from being jitted by numba. Idea is to find a python version of the CG minimiser that can be jitted to give …