Variational Inference for the Indian Buffet Process 0.1

Finale DoshiVelez, Kurt Miller, Jurgen Van Gael — Mon, 04 May 2009 16:03:25 -0000

Matlab code for performing variational inference in the Indian Buffet Process with a linear-Gaussian likelihood model.

We provide two kinds of variational approximations (discussed in depth in the corresponding paper and technical report) that trade-off between the speed and accuracy of the inference. In general, we find that this software outperforms similarly optimised Gibbs samplers for large, complex datasets, but is less efficient for smaller/low-dimensional data. Also provided is code for several (tunable) heuristics for improving the optimisation steps in the inference routines.

Archive includes a toy dataset and a sample test file.

Comment by KonstantinMiller on 2009-07-06 23:19

KonstantinMiller — Mon, 06 Jul 2009 23:19:52 -0000

I think I will try to recommend this post to my friends and family, cuz it's really helpful.

mloss.org Variational Inference for the Indian Buffet Process

Variational Inference for the Indian Buffet Process 0.1

Comment by KonstantinMiller on 2009-07-06 23:19