RoBO
Optimization framework
A Bayesian optimization framework designed to optimize complex functions with robustness and flexibility
RoBO: a Robust Bayesian Optimization framework
483 stars
42 watching
133 forks
Language: Python
last commit: over 5 years ago
Linked from 2 awesome lists
Related projects:
Repository | Description | Stars |
---|---|---|
jungtaekkim/bayeso | A framework for optimizing hyperparameters in machine learning models using Bayesian optimization | 93 |
gudovskiy/autodo | Develops an automated machine learning framework to improve deep learning model performance on biased and noisy data | 24 |
sb-ai-lab/lightautoml | A framework for creating machine learning models with minimal code and customization options | 1,204 |
guopengf/auto-fedrl | A reinforcement learning-based framework for optimizing hyperparameters in distributed machine learning environments. | 15 |
100/solid | A comprehensive framework for solving optimization problems without gradient calculations. | 576 |
automl/hpbandster | A distributed framework for optimizing hyperparameters in machine learning models | 611 |
automl/smac3 | An optimization framework for machine learning hyperparameters | 1,085 |
mysteryresearcher/dasha | A framework for distributed optimization with communication compression and optimal oracle complexity. | 0 |
c-bata/goptuna | A decentralized hyperparameter optimization framework inspired by Optuna. | 260 |
skblaz/autobot | An autoML framework for evolving text representations to support explainable text classification models | 10 |
datacanvasio/hypernets | An automated machine learning framework that simplifies the development of end-to-end AutoML toolkits for various domains. | 266 |
brml/climin | A framework for optimizing machine learning functions using gradient-based optimization methods. | 180 |
fpicetti/occamypy | A library for solving large-scale optimization problems with flexible and scalable vector and operator definitions | 54 |
befelix/safeopt | An algorithmic framework for optimizing performance measures with safety constraints using Bayesian optimization and Gaussian processes. | 141 |
jonfanlab/glonet | A software framework for training neural networks to optimize dielectric metasurfaces using physics-driven generative models and global optimization algorithms. | 101 |