Infinite latent feature models and the Indian buffet process

  title={Infinite latent feature models and the Indian buffet process},
  author={Thomas L. Griffiths and Zoubin Ghahramani},
We define a probability distribution over equivalence classes of binary matrices with a finite number of rows and an unbounded number of columns. This distribution is suitable for use as a prior in probabilistic models that represent objects using a potentially infinite array of features. We derive the distribution by taking the limit of a distribution over N × K binary matrices as K → ∞, a strategy inspired by the derivation of the Chinese restaurant process (Aldous, 1985; Pitman, 2002) as the… CONTINUE READING
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