Protected: Optimization using Lagrangian functions in machine learning (1)
Optimization using Lagrangian functions in machine learning for digital transformation, artificial intelligence, and machine learning tasks (steepest ascent method, Newton method, dual ascent method, nonlinear equality-constrained optimization problems, closed truly convex function f, μ-strongly convex function, conjugate function, steepest descent method, gradient projection method, linear inequality constrained optimization problems, dual decomposition, alternate direction multiplier method, regularization learning problems)