A Birth-Death Process for Feature Allocation
We propose a Bayesian nonparametric prior over feature allocations for sequential data, the birth-death feature allocation process (BDFP). The BDFP models the evolution of the feature allocation of a set of N objects across a covariate (e.g. time) by creating and deleting features. A BDFP is exchang...
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| Format: | Conference item |
| Published: |
Proceedings of Machine Learning Research
2017
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