a lightweight header-only C++17 library of numerical optimization methods for nonlinear functions based on Eigen

OptimLib: a lightweight C++ library of numerical optimization methods for nonlinear functions

LBFGS-Lite: A header-only L-BFGS unconstrained optimizer.

An open source library for the GPU-implementation of L-BFGS-B algorithm

A collection of numerical methods written in Nim

Improved LBFGS and LBFGS-B optimizers in PyTorch.

A C++ toolkit for Convex Optimization (Logistic Loss, SVM, SVR, Least Squares etc.), Convex Optimization algorithms (LBFGS, TRON, SGD, AdsGrad, CG, Nesterov etc.) and Classifiers/Regressors (Logistic Regression, SVMs, Least Squares Regression etc.)

Type-safe modelling DSL, symbolic transformation, and code generation for solving optimization problems.

Federated learning with PyTorch (federated averaging and consensus optimization): with 'reduced' bandwidth

LBFGS optimization algorithm ported from liblbfgs

(Python, Tensorflow, R, C, C++) Stochastic, limited-memory quasi-Newton optimizers (adaQN, SQN, oLBFGS)

The code for vector transport free LBFGS quasi-Newton's optimization on the Riemannian manifolds

Library in Haskell for Dynamically Storing Expressions and Code Generator for Various Non-Linear Optimization Solvers

Basic Implementation of "Developability Of TriangleMeshes" from K. Crane, O. Stein, E. Grinspun

Adversarial Attacks on MNIST

Implementation of numerical optimization algorithms for logistic regression problem.

Visual and quantitative example of Steepest Descent vs limited memory BFGS (Broyden-Fletcher-Goldfarb-Shanno)

C++ port of www.pyrunner.com/weblog/2016/05/26/compressed-sensing-python/