Publication
ECAI 2016
Conference paper

Scalable Exact MAP Inference in Graphical Models

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Abstract

This paper presents parallel dovetailing in a distributed-memory environment for exact MAP inference in graphical models. Parallel dovetailing is a simple procedure which performs multiple searches in parallel with different parameter configurations. We evaluate empirically the performance of parallel dovetailing with three state-of-the-art AND/OR search algorithms in solving various MAP inference benchmarks. Our results clearly show that parallel dovetailing is effective, yielding considerable speedups and improving the solving abilities of these state-of-the-art baseline methods.

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ECAI 2016

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