Welcome to reg4opt 
Docs | Installation | Cite
reg4opt is a Python implementation of operator regression and convex regression methods presented in the paper "OpReg-Boost: Learning to Accelerate Online Algorithms with Operator Regression" by Nicola Bastianello, Andrea Simonetto, Emiliano Dall'Anese.
The documentation is available here.
Installation
reg4opt works on Python 3.7 and depends on: tvopt, numpy, scipy. To run the examples, cvxpy may also be needed.
pip installation
pip install reg4opt
Cite
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Author
reg4opt is developed by Nicola Bastianello under the supervision of Andrea Simonetto and Emiliano Dall'Anese
1 maintainer
Metadata
1 maintainer
Release files for reg4opt 0.1.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
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| reg4opt-0.1.0.tar.gz | 14.6 kB | Details |
Release files / reg4opt-0.1.0.tar.gz
| Download URL | reg4opt-0.1.0.tar.gz |
|---|---|
| Size | 14.6 kB |
| Tags | Source |
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