Learning Link-Probabilities in Causal Trees

📝 Original Info

• Title: Learning Link-Probabilities in Causal Trees
• ArXiv ID: 1304.3103
• Date: 2013-04-12
• Authors: Researchers from original ArXiv paper

📝 Abstract

A learning algorithm is presented which given the structure of a causal tree, will estimate its link probabilities by sequential measurements on the leaves only. Internal nodes of the tree represent conceptual (hidden) variables inaccessible to observation. The method described is incremental, local, efficient, and remains robust to measurement imprecisions.

💡 Deep Analysis

Deep Dive into Learning Link-Probabilities in Causal Trees.

A learning algorithm is presented which given the structure of a causal tree, will estimate its link probabilities by sequential measurements on the leaves only. Internal nodes of the tree represent conceptual (hidden) variables inaccessible to observation. The method described is incremental, local, efficient, and remains robust to measurement imprecisions.

📄 Full Content

Reference