A pure-MATLAB library of EVolutionary (population-based) OPTimization for Large-Scale black-box continuous Optimization (evopt-lso).
-
Updated
Aug 17, 2019 - MATLAB
A pure-MATLAB library of EVolutionary (population-based) OPTimization for Large-Scale black-box continuous Optimization (evopt-lso).
Numerical optimization via mollifier smoothing
Snake SL - Supervised Learning that solves the Snake game. SL was implemented by Gradient-Free-Optimizers library available for Python, neural networks was created in Keras and game was created in Pygame.
Gradient Free Reinforcement Learning solving Openai gym LunarLanderV2 by Evolution Strategy (Genetic Algorithm)
fireworks swarm optimization - efficient derivative free solver.
🥭 MANGO: Maximization of neural Activation via Non-Gradient Optimization
Implementation code for the paper "Bayesian Optimization via Exact Penalty"
A pure-MATLAB library for POPulation-based Large-Scale Black-Box Optimization (pop-lsbbo).
Snake RL - Reinforcement Learning that solves the Snake game. RL was implemented by Gradient-Free-Optimizers library available for Python, neural networks was created in Keras and game was created in Pygame.
ESKit is a portable library written in C, that provides implementations of some self-adaptive evolution strategies
a minimal implementation of the random search algorithm for reinforcement learning.
Gradient free reinforcement learning for PyTorch
A collection and visualization of single objective black-box functions for optimization benchmarking.
Gradient-free online optimization loosely based on Adaptive Moment Estimation (Adam)
Implementation of smoothing-based optimization algorithms
A Julia implementation of Simultaneous Perturbation Stochastic Approximation
Particle Swarm Optimiser
Exploring evolutionary protein fitness landscapes
Zeroth order Frank Wolfe algorithm. Project for the Optimization for Data Science exam.
Black-box adversarial attacks on deep neural networks with tensor train (TT) decomposition and PROTES optimizer.
Add a description, image, and links to the gradient-free-optimization topic page so that developers can more easily learn about it.
To associate your repository with the gradient-free-optimization topic, visit your repo's landing page and select "manage topics."