Coordinate descent method

アルゴリズム:Algorithms

Protected: Statistical Mathematical Theory for Boosting

Statistical and mathematical theory boosting generalized linear model, modified Newton method, log likelihood, weighted least squares method, boosting, coordinate descent method, iteratively weighted least squares method, iteratively reweighted least squares method, IRLS method, weighted empirical discriminant error, parameter update law, Hessian matrix, corrected Newton method, Newton method, Newton method, iteratively reweighted least squares method, IRLS method) used for digital transformation, artificial intelligence, machine learning tasks. iteratively reweighted least square method, IRLS method, weighted empirical discriminant error, parameter update law, Hessian matrix, corrected Newton method, modified Newton method, Newton method, Newton method, link function, logistic loss, logistic loss, boosting algorithm, logit boost, exponential loss, convex margin loss, adaboost, weak hypothesis, empirical margin loss, nonlinear optimization
アルゴリズム:Algorithms

Protected: Conjugate gradient and nonlinear conjugate gradient methods as continuous optimization in machine learning

Conjugate gradient methods as continuous machine learning optimization for digital transformation, artificial intelligence, and machine learning tasks (moment method, nonlinear conjugate gradient method, search direction, inertia term, Polak-Ribiere method, linear search, Wolf condition, Dai-Yuan method, strong Wolf condition, Fletcher-Reeves method, global convergence, Newton method, rapid descent method, Hesse matrix, convex quadratic function, conjugate gradient method, minimum eigenvalue, maximum eigenvalue, affine subspace, conjugate direction method, coordinate descent method)
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