Infinite latent feature models and the Indian buffet process

We define a probability distribution over equivalence classes of binary ma- trices 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 o...更多