On sampling from the Gibbs distribution with random maximum a-posteriori perturbations
In this paper we describe how MAP inference can be used to sample efficiently from Gibbs distributions. Specifically, we provide means for drawing either approximate or unbiased samples from Gibbs' distributions by introducing low dimensional perturbations and solving the corresponding MAP assi...
| Main Authors: | , , |
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| Other Authors: | |
| Format: | Article |
| Language: | en_US |
| Published: |
Neural Information Processing Systems
2015
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| Online Access: | http://hdl.handle.net/1721.1/100400 https://orcid.org/0000-0002-2199-0379 |