the Indian Buffet Process: An Introduction and Review

The Indian Buffet Process (IBP) is one of Bayesian nonparametric models, which is a prior measure on an infinite binary matrix. Unlike the Dirichlet process(DP), where each atom has negative correlation, IBP assumes each atom is independent.

Introduction

IBP is often used in factor analysis as a prior of infinite factors. IBP can be viewed as an extension of DP, where we drop the constraint [math]\displaystyle{ \sum_(i=1)^(\inf){\pi_i}=1 }[/math] .