最適化:Optimization

Statistical Learning Theory

Theory on statistical properties of machine learning algorithms utilized in digital transformation, artificial intelligence, and machine learning tasks (law of large uniform numbers, universal kernel, discriminant fitting loss)

2022.08.13

アルゴリズム:Algorithms微分積分:Calculus最適化:Optimization機械学習:Machine Learning確率・統計:Probability and Statistics線形代数:Linear Algebra集合論:Set theory

Continuous optimization in machine learning

Sequential optimization, an important computational method for constructing machine learning algorithms used in digital transformation artificial intelligence and machine learning tasks

2022.08.12

アルゴリズム:Algorithmsグラフ理論微分積分:Calculus最適化:Optimization機械学習:Machine Learning確率・統計:Probability and Statistics線形代数:Linear Algebra

Protected: Gaussian Processes – The Advantages of Functional Clouds and Their Relationship to Regression Models, Kernel Methods, and Physical Models

Gaussian Processes as Applications of Stochastic Generative Models for Digital Transformation (DX), Artificial Intelligence (AI), and Machine Learning (ML) Tasks Miscellaneous Function Clouds Advantages and Regression Models and their Relationship to Kernel Methods and Physical Models

2022.08.11

アルゴリズム:Algorithmsグラフ理論ベイズ推定微分積分:Calculus最適化:Optimization機械学習:Machine Learning確率・統計:Probability and Statistics線形代数:Linear Algebra

Protected: Structured Support Vector Machines

SVM structure learning and parsing using the deletion plane method algorithm on support vector machines utilized for digital transformation, artificial intelligence, and machine learning tasks, and protein similarity sequence search

2022.08.08

Rアルゴリズム:Algorithms幾何学:Geometry微分積分:Calculus最適化:Optimization機械学習:Machine Learning画像認識技術異常検知・変化検知確率・統計:Probability and Statistics線形代数:Linear Algebra自然言語処理:Natural Language Processing音声信号認識技術

Optimization for the First Time Reading Notes

Optimization for the First Time Reading Notes From Optimization for Beginners This book is explained in d...

2022.08.06

グラフ理論ベイズ推定微分積分:Calculus最適化:Optimization機械学習:Machine Learning深層学習:Deep Learning確率・統計:Probability and Statistics線形代数:Linear Algebra集合論:Set theory

Protected: About Bayesian Statistics and Machine Learning

The impact of machine learning on scientific methodology and engineering, and the suitability of probabilistic statistical approaches, particularly Bayesian models, for machine learning design

2022.08.06

アルゴリズム:Algorithmsグラフ理論ベイズ推定微分積分:Calculus推論技術:inference Technology最適化:Optimization機械学習:Machine Learning確率・統計:Probability and Statistics線形代数:Linear Algebra

Protected: Support vector machine software and implementation

Classification and regression with SVM using R kernlab in support vector machines used for digital transformation, artificial intelligence and machine learning tasks and LIBSVM algorithms SMO algorithm, shrinking

2022.07.29

アルゴリズム:Algorithms微分積分:Calculus最適化:Optimization機械学習:Machine Learning画像認識技術異常検知・変化検知確率・統計:Probability and Statistics線形代数:Linear Algebra自然言語処理:Natural Language Processing関係データ学習音声信号認識技術

Protected: Computing Peripheral Probability Distributions – Mean Field Approximation

Application of graphical models to stochastic generative models utilized in digital transformation, artificial intelligence, and machine learning tasks; approximate computation and algorithms for peripheral probability distributions from variational problems using mean field approximation

2022.07.28

アルゴリズム:Algorithmsグラフ理論ベイズ推定微分積分:Calculus推論技術:inference Technology最適化:Optimization機械学習:Machine Learning確率・統計:Probability and Statistics線形代数:Linear Algebra

Protected: Comparison of clustering using k-means and Bayesian estimation methods (mixed Gaussian model)

Comparison of k-means and Bayesian estimation (mixed Gaussian model) clustering as probabilistic generative models utilized in digital transformation, artificial intelligence , and machine learning tasks

2022.07.26

アルゴリズム:Algorithmsグラフ理論ベイズ推定微分積分:Calculus推論技術:inference Technology最適化:Optimization機械学習:Machine Learning確率・統計:Probability and Statistics線形代数:Linear Algebra

Protected: Overview of Gaussian Processes(5)Generalization of Gaussian Process Regression

Extensions of probabilistic generative models utilized in digital transformation, artificial intelligence, and machine learning tasks and generalizations of the Cauchy distribution of Gaussian processes as robustness collateral, Gaussian process identification models, and Poisson distributions for machine failure, elementary particle decay, etc.

2022.07.25

アルゴリズム:Algorithmsベイズ推定微分積分:Calculus推論技術:inference Technology数理論理学最適化:Optimization機械学習:Machine Learning確率・統計:Probability and Statistics線形代数:Linear Algebra