PyPop7: A Pure-Python Library for POPulation-based Black-Box Optimization (BBO), especially *Large-Scale* variants (including evolutionary algorithms, swarm-based random optimizers, pattern search, and even random search). [https://jmlr.org/papers/v25/23-0386.html (CCF-A)] (Its Planned Extensions: *PyCoPop7*, *PyNoPop7*, *PyPop77*, and *PyMePop7*)

Official implementation for the paper "Model-based Diffusion for Trajectory Optimization". Model-based diffusion (MBD) is a novel diffusion-based trajectory optimization framework that employs a dynamics model to run the reverse denoising process to generate high-quality trajectories.

Square Attack: a query-efficient black-box adversarial attack via random search [ECCV 2020]

Elo ratings for global black box derivative-free optimizers

Official implementation for the paper "CoVO-MPC: Theoretical Analysis of Sampling-based MPC and Optimal Covariance Design" accepted by L4DC 2024. CoVO-MPC is an optimal sampling-based MPC algorithm.

Powell's Derivative-Free Optimization solvers.

[ICML 2024] Official code for the paper "Revisiting Zeroth-Order Optimization for Memory-Efficient LLM Fine-Tuning: A Benchmark ".

[ICLR'24] "DeepZero: Scaling up Zeroth-Order Optimization for Deep Model Training" by Aochuan Chen*, Yimeng Zhang*, Jinghan Jia, James Diffenderfer, Jiancheng Liu, Konstantinos Parasyris, Yihua Zhang, Zheng Zhang, Bhavya Kailkhura, Sijia Liu

This repository contains the PyTorch implementation of Zeroth Order Optimization Based Adversarial Black Box Attack (https://arxiv.org/abs/1708.03999)

Robustify Black-Box Models (ICLR'22 - Spotlight)

Every Call is Precious: Global Optimization of Black-Box Functions with Unknown Lipschitz Constants

Code for IEEE MLSP 2021 paper titled "Model-Free Learning of Optimal Deterministic Resource Allocations in Wireless Systems via Action-Space Exploration"

Zeroth-Order Regularized Optimization (ZORO): Approximately Sparse Gradients and Adaptive Sampling

Benchmarking optimization solvers.

SCOBO: Sparsity-aware Comparison Oracle Based Optimization

Hard-Thresholding Meets Evolution Strategies in Reinforcement Learning

Implementation of the algorithms described in the papers "ZO-AdaMM: Zeroth Order Adaptive Momentum" by Chen et al., "Stochastic first- and zeroth-order methods" by Ghadimi et al. and "SignSGD via zeroth- order oracle" by Liu et al.

Blockwise Direct Search (MATLAB version)

Modular optimization library for PyTorch.

Nevergrad Optimizer Benchmarking for 3D Performance Capture