Convergence Rate

アルゴリズム:Algorithms

Protected: Stochastic coordinate descent as a distributed process for batch stochastic optimization

Stochastic coordinate descent as a distributed process for batch stochastic optimization utilized in digital transformation, artificial intelligence, and machine learning tasks (COCOA, convergence rate, SDCA, γf-smooth, approximate solution of subproblems, stochastic coordinate descent, parallel stochastic coordinate descent, parallel computing process, Communication-Efficient Coordinate Ascent, dual coordinate descent)
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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Protected: On-line Stochastic Optimization and Stochastic Dual Averaging (SDA) for Machine Learning

On-line stochastic optimization and stochastic dual averaging methods for machine learning (mirror image descent, strongly convex functions, convex functions, convergence rates, polynomial decay averaging, strongly convex regularization) for digital transformation, artificial intelligence and machine learning tasks.
アルゴリズム:Algorithms

Protected: Online Stochastic Optimization and Stochastic Gradient Descent for Machine Learning

Stochastic optimization and stochastic gradient descent methods for machine learning for digital transformation DX, artificial intelligence AI and machine learning ML task utilization
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