グラフ理論

Symbolic Logic

Protected: Basics of Statistical Causal Effects (2)Methods Using Regression Models and Matching and Stratified Analysis

Regression modeling methods for statistical causal inference utilized in digital transformation, artificial intelligence, and machine learning tasks; causal effect estimation using matching and stratified analysis methods
2022.03.30
Symbolic Logicグラフ理論推論技術:inference Technology数理論理学最適化:Optimization機械学習:Machine Learning確率・統計:Probability and Statistics
Symbolic Logic

Protected: Basics of Statistical Causal Effects (1)Definition of Causal Effects Based on the Rubin Effect Model

Definition of causal effects and estimation of statistical causal effects (ATT, ATU, ATE) based on the Rubin effect model used for digital transformation, artificial intelligence and machine learning tasks
2022.03.29
Symbolic Logicグラフ理論推論技術:inference Technology数理論理学最適化:Optimization機械学習:Machine Learning確率・統計:Probability and Statistics
グラフ理論

Machine Learning Professional Series – Gaussian Processes and Machine Learning Reading Notes

Summary A Gaussian Process (GP) is a nonparametric regression and classification method based on probability th...
2022.03.27
グラフ理論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関係データ学習
Symbolic Logic

From Inductive logic Programming 2012 Proceedings

Machine Learning Technology  Artificial Intelligence Technology  Natural Language Processing Technology  Semantic Web Te...
2022.03.27
Symbolic Logicエキスパートシステム:expertsystemグラフ理論セマンテックウェブ技術:Semantic web Technology情報理論/計算理論推論技術:inference Technology最適化:Optimization検索技術:Search Technology
Symbolic Logic

Protected: Quasi-experimental design – how to derive causal relationships from observed data

How to verify causality for digital transformation, artificial intelligence , and machine learning tasks by first having the data for causal inference and then verifying causality from there.
2022.03.25
Symbolic Logicグラフ理論推論技術:inference Technology数理論理学機械学習:Machine Learning確率・統計:Probability and Statistics関係データ学習
Symbolic Logic

Protected: Correlation, Causation and Relational Structure (2) Backdoor Criteria

Actual backdoor criteria for narrowing down variables to observe intervention effects in causal inference for digital transformation , artificial intelligence, and machine learning tasks
2022.03.23
Symbolic Logicグラフ理論ベイズ推定推論技術:inference Technology数理論理学最適化:Optimization機械学習:Machine Learning確率・統計:Probability and Statistics
Symbolic Logic

Protected: Discrepancy between correlation (regression coefficient) and causation (intervention effect)

Differences between regression coefficients and intervention effect values for digital transformation, artificial intelligence , and machine learning tasks.
2022.03.22
Symbolic Logicグラフ理論推論技術:inference Technology数理論理学最適化:Optimization機械学習:Machine Learning確率・統計:Probability and Statistics関係データ学習
Symbolic Logic

Machine Learning Professional Series “Submodular Optimization and Machine Learning” reading notes

  Machine Learning Professional Series "Submodular Optimization and Machine Learning" reading notes Submodular f...
2022.03.21
Symbolic Logicアルゴリズム:Algorithmsグラフ理論推論技術:inference Technology数理論理学最適化:Optimization機械学習:Machine Learning確率・統計:Probability and Statistics
グラフ理論

Bayesian inference and MCMC open source software

Bayesian inference and MCMC open source software Bayesian statistics means that not only the data, but also th...
2022.03.20
グラフ理論ベイズ推定推論技術:inference Technology数理論理学最適化:Optimization機械学習:Machine Learning確率・統計:Probability and Statistics
グラフ理論

Machine Learning Startup Series – Introduction to Machine Learning with Bayesian Inference Reading Notes

Summary Bayesian estimation can be one of the statistical methods for interpreting data and learning models fro...
2022.03.20
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
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