Codes for primal-dual method with linesearch
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Updated
Apr 3, 2017 - Jupyter Notebook
Codes for primal-dual method with linesearch
Visualize common algorithms using python
Implementation of numerical optimization algorithms for logistic regression problem.
Text Statistics For Node Streams
Golden Section, Quadratic Interpolation, Nelder-Mead line search algorithms are studied.
Implementation of a Neural Network with L-BFGS with Line Search and Gradient Descent with Momentum for numerical optimization purposes
Line Search optimization of several 2D functions demonstrating the usage of Gradient Descent and Hessian direction with Wolfe condition
Provides line search methods, such as backtracking, to determine the optimal step size in optimization and root-finding algorithms.
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Collection of line search techniques
Easy-to-use linear and non-linear solver
Convex, Nonsmooth, Nonlinear Optimization Solver and Problems
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