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

[JMLR-2024] PyPop7: A Pure-Python Library for POPulation-based Black-Box Optimization (BBO), especially their *Large-Scale* versions/variants (-> evolutionary algorithms/swarm-based optimizers/pattern search/random search/...).

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

Python library for Bayesian hyper-parameters optimization

Heuristic Optimization for Python

Sparse-RS: a versatile framework for query-efficient sparse black-box adversarial attacks

Cross Validation, Grid Search and Random Search for TensorFlow 2 Datasets

A simple JAX-based implementation of random search for locomotion tasks using MuJoCo XLA (MJX).

A simple random searching technique which provides a competitive approach to Reinforcement learning for Locomotion related tasks on Mu-Jo-Co bodies like Humanoid, Half-Cheetah etc

These are Stochastic Optimization Codes by using various Techniques to optimize the function/Feature Selection

Global optimization by uniform random global search

The repository includes the Augmented Random Search algorithm implemented from scratch in Python. This AI algorithm as released on March 2018 research paper is a faster and more efficient than other reinforcement algorihtms.

Brute Force Architecture Search

A simple n-dimensional random search algorithm

Open-Source Optimization Library - Extremum

Code for Quora Competition on Kaggle

Solving n-queen problem using Python programming language

This package is an automatic machine learning module whose function is to optimize the hyper-parameters of an automatic learning model.

An AutoRecSys Library built around LensKit. Performs automatic algorithm selection, hyperparameter optimzation and ensembling on LensKit models.

This project focuses on analyzing patient feedback regarding the treatment provided by home healthcare service agencies.