a lightweight header-only C++17 library of numerical optimization methods for nonlinear functions based on Eigen
-
Updated
Jan 3, 2024 - C++
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
Here I upload my ML test scripts written in MATLAB or Python
Adversarial Attacks on MNIST
Implementation of numerical optimization algorithms for logistic regression problem.
Add a description, image, and links to the lbfgs topic page so that developers can more easily learn about it.
To associate your repository with the lbfgs topic, visit your repo's landing page and select "manage topics."