Hierarchical Bayesian Model

Protected: Individuality and parameter estimation (Interpreting the Hierarchical Bayesian Model)

Relationship between global parameter estimation and local parameters (e.g., individual differences) for understanding hierarchical Bayesian models.

2021.10.19

推論技術:inference Technology機械学習:Machine Learning確率・統計:Probability and Statistics

Protected: Capturing “Individuality” with Hierarchical Models (Hierarchical Bayesian Models and Empirical Bayesian Methods (GLMM))

Understanding "personality" in hierarchical Bayesian models and solving with empirical Bayesian methods (GLMM), which can be used for artificial intelligence (AI), natural language processing, and digital transformation (DX).

2021.10.11

機械学習:Machine Learning確率・統計:Probability and Statistics