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
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)
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