gradient-free-optimization

Simple and reliable optimization with local, global, population-based and sequential techniques in numerical discrete search spaces.

Distributed GPU-Accelerated Framework for Evolutionary Computation. Comprehensive Library of Evolutionary Algorithms & Benchmark Problems.

[JMLR (CCF-A)] PyPop7: A Pure-Python LibrarY for POPulation-based Black-Box Optimization (BBO), especially *Large-Scale* variants (from evolutionary computation, swarm intelligence, statistics, operations research, machine learning, mathematical optimization, etc.). [https://jmlr.org/papers/v25/23-0386.html]

ACL'2023: Multi-Task Pre-Training of Modular Prompt for Few-Shot Learning

Gradient-free optimization method for multivariable functions based on the low rank tensor train (TT) format and maximal-volume principle.

Gradient-free optimization method for the multidimensional arrays and discretized multivariate functions based on the tensor train (TT) format.

A python package for consensus-based optimization

Tutorials for the optimization techniques used in Gradient-Free-Optimizers and Hyperactive.

Deep Neural Network Optimization Platform with Gradient-based, Gradient-Free Algorithms

Markov Chain Monte Carlo binary network optimization

🥭 MANGO: Maximization of neural Activation via Non-Gradient Optimization

EvoRBF: A Nature-inspired Algorithmic Framework for Evolving Radial Basis Function Networks

Modular optimization library for PyTorch (work-in-progress).

Gradient free reinforcement learning for PyTorch

Surrogate-based 0-th Order Global Optimization for black-box problems.

Blockwise Direct Search (MATLAB version)

Black-box adversarial attacks on deep neural networks with tensor train (TT) decomposition and PROTES optimizer.

Implementation of smoothing-based optimization algorithms

Implementation code for the paper "Bayesian Optimization via Exact Penalty"

A collection and visualization of single objective black-box functions for optimization benchmarking.