pbo
Gradient-Free-Optimizers
| pbo | Gradient-Free-Optimizers | |
|---|---|---|
| 1 | 11 | |
| 14 | 1,119 | |
| - | - | |
| 3.0 | 8.5 | |
| 8 months ago | 10 days ago | |
| Python | Python | |
| MIT License | MIT License |
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pbo
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Why we use diagonal gaussian rather than multivariate guassian (with full covariance matrix)
I have implemented full covariance matrix output from neural networks in a drl-related project, in which I devised an optimization technique out of mixing a PG approach with CMA-ES concepts, and you can find a possible implementation of how to do so here: https://github.com/jviquerat/pbo In this specific context, full covariance matrix gave a very significant performance boost. Yet I don't want to draw premature conclusions on whether this will end up the same when plugged into PPO.
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?
Hyperactive - An optimization and data collection toolbox for convenient and fast prototyping of computationally expensive models.
opytimizer - 🐦 Opytimizer is a Python library consisting of meta-heuristic optimization algorithms.
surrogate-models - A collection of surrogate models for sequence model based optimization techniques
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
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.
PSO-cont-sched - Made for a college project, this Java program attempts to demonstrate how PSO might be used to solve container scheduling problems.
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.
Signal-Desktop - A private messenger for Windows, macOS, and Linux.
vizier - Python-based research interface for blackbox and hyperparameter optimization, based on the internal Google Vizier Service.
sigopt-server - Open Source version of SigOpt API, performing hyperparameter optimization and visualization