OptimLib: a lightweight C++ library of numerical optimization methods for nonlinear functions
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Updated
Apr 28, 2024 - C++
OptimLib: a lightweight C++ library of numerical optimization methods for nonlinear functions
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.)
An R package for large scale estimation with stochastic gradient descent
A next-gen solver for optimization with nonconvex objective and constraints. Reimplements filterSQP and IPOPT (barrier) in a modern and generic way, and unlocks a variety of novel methods. Competitive against filterSQP, IPOPT, SNOPT, MINOS and CONOPT.
A single header-only C++ library for least squares fitting.
Density Functional Theory with plane waves basis, applied on a 'quantum dot'. Volumetric visualization of orbitals with VTK
The first challenge of PACS course. It is a code which finds the local minimum of an analytic function in n dimensions using various gradient descent techniques. For 2D, it also provides a plot of the iterations, and how they oscillate before reaching the minimum.
A simple convolutional network to classify handwritten digits
OpenCL Logistic Regression with gradient ascent
A simple demonstration of gradient-descent algorithm in C++ on a linear funciton.
To understand neural networks thoroughly I implemented them from scratch in C++. This is the source code for the same.
Mini-project codes: Java, C++, Matlab, OpenMP, MPI, OpenCL, p_thread and Assembly Language.
Implementation of linear regression algorithm from Stanford's machine learning course
Different type of solvers to solve systems of nonlinear equations
A simple feedforward neural network implementation in C++.
A Deep feed forward neural network that learns the MNIST dataset for digit classification...
Real-time solution to the target guarding problem using constrained optimization
Training diverse kind of neural nets architectures with C++
Gradient descent for estimating inbreeding spatial coefficients from pairwise-IBD estimates
gradient-based symbolic execution engine implemented from scratch
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