グラフ理論

アルゴリズム:Algorithms

Overview of statistical learning theory (explanation without mathematical formulas)

On the theory of statistical properties of machine learning algorithms The theory of the statistical properties...
アルゴリズム:Algorithms

Protected: Upper Bound Minimization Algorithm as Sequential Optimization in Machine Learning

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Protected: Optimization Using Lagrangian Functions in Machine Learning (3)Alternate Direction Multiplier Method

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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
python

Overview and implementation of stochastic optimization in machine learning

Overview of Stochastic Optimization in Machine Learning Stochastic optimization represents a method of solvin...
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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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 ...
アルゴリズム:Algorithms

Overview of combinatorial optimization and libraries and reference books for implementation

  What is a combinatorial optimization problem? Combinatorial optimization theory has been applied to many real...
Clojure

Overview of generalized linear models and their implementation in various languages

Generalized Linear Model Overview The Generalized Linear Model (GLM) is a statistical modeling and machin...
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