Code for comparing ADMM and an interior-point method, as presented in Hinge-Loss Markov Random Fields and Probabilistic Soft Logic and my Ph.D. dissertation. It also contains the data and setup for the paper Scaling MPE Inference for Constrained Continuous Markov Random Fields with Consensus Optimization, but this code tests the improved version of the inference algorithm for piecewise-quadratic problems.
Please cite this work as
@article{bach:arxiv15,
Title = {Hinge-Loss Markov Random Fields and Probabilistic Soft Logic},
Author = {Bach, Stephen H. and Broecheler, Matthias and Huang, Bert and Getoor, Lise},
Volume = {arXiv:1505.04406 [cs.LG]},
Year = {2015}}
This software depends on Java 6+ and Maven 3. Python (>=2.7) is also required to process the results.
Running the experiment also requires installing the MOSEK add-on for PSL. Please follow the instructions.
The algorithms for this experiment are implemented in the PSL library, version 1.2. It will be downloaded by Maven automatically.
The experiment can be run by executing run.sh.