A Novel Approach for Constrained Optimization in Graphical Models
Authors: Sara Rouhani, Tahrima Rahman, Vibhav Gogate
NeurIPS 2020 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Our experiments show that our algorithms are superior to the following approach: encode the problem as a mixed integer linear program (MILP) and solve the latter using a state-of-the-art MILP solver such as SCIP. |
| Researcher Affiliation | Academia | Sara Rouhani, Tahrima Rahman and Vibhav Gogate The University of Texas at Dallas {sara.rouhani,tahrima.rahman,vibhav.gogate}@utdallas.edu |
| Pseudocode | Yes | Algorithm 1 ANYTIME-CMPE (M1, M2, q, k) |
| Open Source Code | No | The paper mentions using SCIP [13], a state-of-the-art open source MILP solver, but does not provide specific access to the authors' own implementation code for the methodology described. |
| Open Datasets | Yes | We experimented with the following benchmark graphical models, available from the UAI 2010 and 2014 competitions [11, 16] |
| Dataset Splits | No | The paper mentions using benchmark graphical models but does not provide specific information about training, validation, or test dataset splits. |
| Hardware Specification | No | No specific hardware details (such as GPU/CPU models or memory specifications) used for running the experiments are mentioned in the paper. |
| Software Dependencies | Yes | We compared the performance of Algorithm ANYTIME-CMPE with SCIP [13], a state-of-the-art open source mixed integer linear programming (MILP) solver. ... The SCIP Optimization Suite 7.0. |
| Experiment Setup | Yes | We experimented with the following five values of k: {1, 3, 5, 7, 9}. For each k, we ran our algorithm on each probabilistic network for 1200 seconds. SCIP was also run for 1200 seconds on each network. ... We used restart-based local search to perform search over the value assignments to S. ... We implemented the greedy MCKP algorithm of [14] to solve Ps. ... We used the max-degree heuristic outlined in section 4.2 to select a minimal k-separator. |