Skip to content

Commit 99e4454

Browse files
sagar1sharmasagar2190sharmabenjamc
authored
Added ecosystem information in documentation (#1272)
* Added ecosystem information in documentation * Changed formatting from bullet points to sentences * Update index.md --------- Co-authored-by: sagar1sharma <[email protected]> Co-authored-by: C. Benjamins <[email protected]>
1 parent e9d71a5 commit 99e4454

File tree

1 file changed

+17
-0
lines changed

1 file changed

+17
-0
lines changed

docs/index.md

Lines changed: 17 additions & 0 deletions
Original file line numberDiff line numberDiff line change
@@ -9,6 +9,23 @@ SMAC is a tool for algorithm configuration to optimize the parameters of arbitra
99

1010
SMAC3 is written in Python3 and continuously tested with Python 3.8, 3.9, and 3.10. Its Random Forest is written in C++. In the following, SMAC is representatively mentioned for SMAC3.
1111

12+
## Ecosystem
13+
14+
SMAC3 integrates with several tools in the AutoML ecosystem to enhance hyperparameter optimization workflows:
15+
16+
### DeepCAVE
17+
[DeepCAVE](https://github.com/automl/DeepCAVE) is an interactive visualization tool for optimization. It provides advanced plotting and analysis of SMAC runs, enabling users to efficiently generate insights for AutoML problems. DeepCAVE brings the human back into the loop with its intuitive graphical user interface.
18+
19+
### CARPS
20+
[CARPS](https://github.com/carps-ai/carps) (Configuration And Running Parallel Systems) is a framework for benchmarking and parallelizing optimization methods. It offers a lightweight interface between optimizers and benchmarks, supports native SMAC3 integration, and includes many HPO tasks from various domains such as black-box, multi-fidelity, multi-objective, and multi-objective multi-fidelity optimization.
21+
22+
### HyperSweeper
23+
[HyperSweeper](https://github.com/automl/HyperSweeper) is designed for efficient hyperparameter optimization of large models, especially when objective functions are expensive to evaluate. It supports distributed computation on clusters (using Slurm, Joblib, or Ray) and evaluates functions as separate jobs for scalability.
24+
25+
### Optuna Integration
26+
SMAC3 is available as a sampler in [Optuna](https://optuna.org/), allowing users to leverage SMAC's optimization strategies within Optuna's flexible framework for hyperparameter optimization.
27+
28+
1229
## Features
1330

1431
* Open source + active maintenance

0 commit comments

Comments
 (0)