Goto

Collaborating Authors

 lrc2cpp

Knowledge Compilation for Lifted Probabilistic Inference: Compiling to a Low-Level Language

Kazemi, Seyed Mehran (University of British Columbia) | Poole, David (University of British Columbia)

AAAI Conferences

Algorithms based on first-order knowledge compilation are currently the state-of-the-art for lifted inference. These algorithms typically compile a probabilistic relational model into an intermediate data structure and use it to answer many inference queries. In this paper, we propose compiling a probabilistic relational model directly into a low-level target (e.g., C or C++) program instead of an intermediate data structure and taking advantage of advances in program compilation. Our experiments represent orders of magnitude speedup compared to existing approaches.

  Country:
  Technology:

Add feedback