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AAAI 2017

Latent Tree Analysis

Conference Paper Senior Member Summary Talks Artificial Intelligence

Abstract

Latent tree analysis seeks to model the correlations amonga set of random variables using a tree of latent variables. It was proposed as an improvement to latent class analysisÑa method widely used in social sciences and medicine to identify homogeneous subgroups in a population. It provides new and fruitful perspectives on a number of machine learningareas, including cluster analysis, topic detection, and deep probabilistic modeling. This paper gives an overview of the research on latent tree analysis and various ways it is used inpractice.

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Context

Venue
AAAI Conference on Artificial Intelligence
Archive span
1980-2026
Indexed papers
28718
Paper id
542757467510980593