GPflowOpt
Gradient-Free-Optimizers
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| GPflowOpt | Gradient-Free-Optimizers | |
|---|---|---|
| 1 | 11 | |
| 263 | 1,103 | |
| 0.0% | - | |
| 1.8 | 5.0 | |
| over 3 years ago | 27 days ago | |
| Python | Python | |
| Apache License 2.0 | MIT License |
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GPflowOpt
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[D] Choosing best parameters from an optimization
1- Hyperparameter optimization as already suggested by u/sener87 but I think your validation does not have to be change as it tests generalization as far as I understand you right. If you have more parameter/larger search space, you may look into Bayesian optimization for this task as implemented e.g. with tensorflow, torch or numpy frameworks.
Gradient-Free-Optimizers
- Show HN: Gradient-Free-Optimizers supports constrained optimization in v1.3
- Gradient-Free-Optimizers version 1.2 released
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Gradient-Free-Optimizers A collection of modern optimization methods in Python
I would be very disappointed if that were the case.. no, it looks like it’s set up to capture variance. The BO algo wraps an “Expected Improvement Optimizer”:
https://github.com/SimonBlanke/Gradient-Free-Optimizers/blob...
Which selects new points based on both the model’s mean estimate and its variance. See around line 58
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Hacker News top posts: Feb 28, 2021
Gradient-Free-Optimizers A collection of modern optimization methods in Python\ (0 comments)
- SimonBlanke/Gradient-Free-Optimizers A collection of modern optimization methods in Python
- Gradient-Free-Optimizers: A collection of modern optimization methods in Python
- Optimize any Python function with modern algorithms in numerical search spaces
What are some alternatives?
modAL - A modular active learning framework for Python
Hyperactive - An optimization and data collection toolbox for convenient and fast prototyping of computationally expensive models.
agents - TF-Agents: A reliable, scalable and easy to use TensorFlow library for Contextual Bandits and Reinforcement Learning.
opytimizer - 🐦 Opytimizer is a Python library consisting of meta-heuristic optimization algorithms.
pybobyqa - Python-based Derivative-Free Optimization with Bound Constraints
optimization-tutorial - Tutorials for the optimization techniques used in Gradient-Free-Optimizers and Hyperactive.
urh - Universal Radio Hacker: Investigate Wireless Protocols Like A Boss
surrogate-models - A collection of surrogate models for sequence model based optimization techniques
prima - PRIMA is a package for solving general nonlinear optimization problems without using derivatives. It provides the reference implementation for Powell's derivative-free optimization methods, i.e., COBYLA, UOBYQA, NEWUOA, BOBYQA, and LINCOA. PRIMA means Reference Implementation for Powell's methods with Modernization and Amelioration, P for Powell.
Signal-Desktop - A private messenger for Windows, macOS, and Linux.
RocketLander - A simple framework equipped with optimization algorithms, such as reinforcement learning, evolution strategies, genetic optimization, and simulated annealing, to enable an orbital rocket booster to land autonomously.