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数理論理学

Gendai Shiso July 2020 Special Feature: The World of Sphere Theory — The Forefront of Modern Mathematics Reading Memo

Application of abstraction using sphere theory, an important theory in modern mathematics, to areas such as physics, computer science, biology, linguistics, and aesthetics.
2021.12.18
数理論理学
機械学習:Machine Learning

Topic Model Theory and Implementation

A topic model is a probability generation model for extracting topics from sentences, which is one of the natural language processing technologies used in digital transformation and artificial intelligence tasks.
2021.12.17
機械学習:Machine Learning確率・統計:Probability and Statistics自然言語処理:Natural Language Processing
微分積分:Calculus

Protected: Change detection by density ratio estimation – Detection of structural changes using the Kullback-Leibler density ratio estimation method

Detecting structural changes using the Kullback-Leibler density ratio estimation method for digital transformation and artificial intelligence tasks.
2021.12.17
微分積分:Calculus推論技術:inference Technology最適化:Optimization機械学習:Machine Learning異常検知・変化検知確率・統計:Probability and Statistics
微分積分:Calculus

Protected: Anomaly detection by density ratio estimation – Anomaly Estimation from Unsupervised Data Using the Kullback-Leibler Density Ratio Estimation Method

Among the anomaly/change detection techniques used in digital transformation and artificial intelligence tasks, I will introduce a method for anomaly detection using probability density ratio for unsupervised data ,Kullback-Leibler density ratio estimation method
2021.12.16
微分積分:Calculus推論技術:inference Technology最適化:Optimization機械学習:Machine Learning異常検知・変化検知確率・統計:Probability and Statistics
微分積分:Calculus

Protected: Anomaly detection using sparse structure learning- Graph models and regularization that link broken dependencies between variables to anomalies.

Graph models and regularization that link broken dependencies between variables to anomalies.
2021.12.15
微分積分:Calculus推論技術:inference Technology最適化:Optimization機械学習:Machine Learning異常検知・変化検知確率・統計:Probability and Statistics
微分積分:Calculus

Protected: Change detection using subspace method -Singular spectral transform method for time series data

Singular spectral transform (SVD) method for extracting change points from time series data for digital transformation and artificial intelligence tasks.
2021.12.14
微分積分:Calculus推論技術:inference Technology最適化:Optimization機械学習:Machine Learning異常検知・変化検知確率・統計:Probability and Statistics
微分積分:Calculus

Protected: Anomaly Detection by Gaussian Process Regression -Output anomaly detection for input, application to design of experiments

Detection of how much the output corresponding to the input is abnormal by Gaussian process regression, one of the most versatile methods of anomaly detection used in digital transformation and artificial intelligence tasks (application to design of experiments).
2021.12.13
微分積分:Calculus推論技術:inference Technology最適化:Optimization機械学習:Machine Learning異常検知・変化検知確率・統計:Probability and Statistics
情報理論/計算理論

Overview of Shannon’s Information Theory and Reference Books

An Introduction to Shannon's Information Theory as a Basis for Artificial Intelligence Technology
2021.12.12
情報理論/計算理論
アルゴリズム:Algorithms

Turing’s Theory of Computation Overview and Reference Books and Neural Turing Machines

An introduction to Turing's theory of computation, the basic computer theory on which artificial intelligence technology is based.
2021.12.12
アルゴリズム:Algorithms情報理論/計算理論数理論理学:Mathematical logic
機械学習:Machine Learning

Machine Learning Prootional Series – Support Vector Machines Reading Notes

Reading notes for a reference book on support vector machines (SVMs), a supervised learning pattern recognition model used for classification and regression in digital transformation, artificial intelligence, and machine learning tasks.
2021.12.12
機械学習:Machine Learning
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