regularization term

アルゴリズム:Algorithms

Protected: Evaluation of Rademacher Complexity and Prediction Discrimination Error in Multi-Valued Discrimination Using Statistical Mathematics Theory

Rademacher Complexity and Prediction Discriminant Error in Multivalued Discrimination by Statistical Mathematics Theory Used in Digital Transformation, Artificial Intelligence and Machine Learning Tasks Convex quadratic programming problems, mathematical programming, discriminant machines, prediction discriminant error, Bayesian error, multilevel support vector machines, representation theorem,. Rademacher complexity, multilevel marginals, regularization terms, empirical loss, reproducing nuclear Hilbert spaces, norm constraints, Lipschitz continuity, predictive Φp-multilevel marginals loss, empirical Φ-multilevel marginals loss, uniform bounds, discriminant functions, discriminant
アルゴリズム:Algorithms

Protected: Optimization methods for L1-norm regularization for sparse learning models

Optimization methods for L1-norm regularization for sparse learning models for use in digital transformation, artificial intelligence, and machine learning tasks (proximity gradient method, forward-backward splitting, iterative- shrinkage threshholding (IST), accelerated proximity gradient method, algorithm, prox operator, regularization term, differentiable, squared error function, logistic loss function, iterative weighted shrinkage method, convex conjugate, Hessian matrix, maximum eigenvalue, second order differentiable, soft threshold function, L1 norm, L2 norm, ridge regularization term, η-trick)
アルゴリズム:Algorithms

Protected: Batch Stochastic Optimization – Stochastic Variance-Reduced Gradient Descent and Stochastic Mean Gradient Methods

Batch stochastic optimization for digital transformation, artificial intelligence, and machine learning tasks - stochastic variance reduced gradient descent and stochastic mean gradient methods (SAGA, SAG, convergence rate, regularization term, strongly convex condition, improved stochastic mean gradient method, unbiased estimator, SVRG, algorithm, regularization, step size, memory efficiency, Nekaterov's acceleration method, mini-batch method, SDCA)
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