`

Timezone: »

 
Poster
Gibbs-type Indian Buffet Processes
Creighton Heaukulani · Daniel Roy

Thu Dec 11 11:00 AM -- 03:00 PM (PST) @ Level 2, room 210D #None
in Poster Session »

We investigate a class of feature allocation models that generalize the Indian buffet process and are parameterized by Gibbs-type random measures. Two existing classes are contained as special cases: the original two-parameter Indian buffet process, corresponding to the Dirichlet process, and the stable (or three-parameter) Indian buffet process, corresponding to the Pitman--Yor process. Asymptotic behavior of the Gibbs-type partitions, such as power-laws holding for the number of latent clusters, translates into analogous characteristics for this class of Gibbs-type feature allocation models. We derive a number of properties of these models, present a black-box inference procedure, and elucidate the subtle differences between this superclass and its better known subclasses.

Author Information

Creighton Heaukulani (Unaffiliated)
Daniel Roy (University of Toronto)

More from the Same Authors