アルゴリズム:Algorithms Protected: Optimization Using Lagrangian Functions in Machine Learning (3)Alternate Direction Multiplier Method
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数学:Mathematics
アルゴリズム:Algorithms アルゴリズム:Algorithms 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)
アルゴリズム:Algorithms Protected: Optimization Using Lagrangian Functions in Machine Learning (2) Extended Lagrangian Method
Overview of optimization methods and algorithms using extended Lagrangian function methods in machine learning for digital transformation, artificial intelligence, and machine learning tasks proximity point algorithm, strongly convex, linear convergence, linearly constrained convex optimization problems, strong duality theorem, steepest descent method, Moreau envelope, conjugate function, proximity mapping, dual problem, dual ascent method, penalty function method, barrier function method
アルゴリズム:Algorithms Protected: Fundamentals of convex analysis in stochastic optimization (2) Fenchel’s dual theorem, proximity maps and strongly convex functions
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アルゴリズム:Algorithms Overview of python Keras and examples of its application to basic deep learning tasks
Summary
This section provides an overview of python Keras and specific applications to basic deep learning ...
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About Probability and Statistics
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Huggingface
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アルゴリズム:Algorithms Example implementation for general time series analysis using R or Python
Overview of time series data analysis
Time-series data is called data whose values change over time, suc...