最適化:Optimization

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
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.
IOT技術:IOT Technology

Submodular Optimization and Machine Learning

Overview of Machine Learning with Submodular Optimization Submodular functions are a concept corresponding to c...
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...
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...
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...
Symbolic Logic

From Inductive logic Programming 2011 Proceedings

Machine Learning Technology  Artificial Intelligence Technology  Natural Language Processing Technology  Semantic Web Te...
Symbolic Logic

Protected: Causal InferenceIntroduction(2)Stratified Analysis and Regression Modeling

Theory and practice of causal inference through analysis by stratified analysis and regression models for statistical causal estimation used in digital transformation , artificial intelligence , and machine learning tasks
Symbolic Logic

Protected: Introduction to Causal Inference (1) Confounding Factors and Randomized Experiments

Introduction to statistical causal inference (randomized experiments controlling for confounding factors to distinguish between causality and pseudo-correlation)
グラフ理論

The World of Bayesian Modeling

  Overview This presentation provides an overview of the contemporary world of Bayesian modeling from the perspec...
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