Derivative-Free Optimization (DFO) algorithm for noisy convex functions which leverages active subspaces for efficiency
Please see our corresponding paper and technical report on arXiv
- If you do not have a computational environment set up to run Python, download Anaconda
- You'll need to clone the active subspaces library, updated to Python 3 by Varis, using
git clone https://github.com/variscarey/active_subspaces_py3.git
in a destination of your choosing (executed in terminal) - Inside the active_subspaces_py3 directory you've just created, run
python setup.py install
(executed in terminal) - Be sure to navigate outside of active_subspaces_py3 in your terminal before the next step
- Next, clone this ASTARS repo locally, using
git clone [email protected]:jordanrhall/ASTARS.git
in a destination of your choosing (executed in terminal) - Inside the ASTARS directory you've just created, run
python setup.py install
(executed in terminal)
Now you should be able to run any of our examples stored in paper_examples.
e.g., Navigate to paper_examples in terminal and run python paper_examples.py
(executed in terminal)
Enjoy!