Published March 11, 2019
| Version v1.0.0-beta
Software
Open
IGITUGraz/L2L: v1.0.0-beta
Authors/Creators
- 1. Technische Universität Graz
- 2. Jülich Research Center
- 3. Universität Bern
Description
The L2L (Learning-to-learn) gradient-free optimization framework contains well documented and tested implementations of various gradient free optimization algorithms. It also defines an API that makes it easy to optimize (hyper-)parameters for any task (optimizee). All the implementations in this package are parallel and can run across different cores and nodes (but equally well on a single core). It includes integration with the JUBE framework, which allows running this framework on HPC clusters.
Files
IGITUGraz/L2L-v1.0.0-beta.zip
Files
(242.3 kB)
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Additional details
Related works
- Is supplement to
- https://github.com/IGITUGraz/L2L/tree/v1.0.0-beta (URL)