Fast Algorithms for Relational Marginal Polytopes
Authors: Yuanhong Wang, Timothy van Bremen, Juhua Pu, Yuyi Wang, Ondrej Kuzelka
IJCAI 2021 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | We demonstrate the efficiency of the proposed approaches experimentally, and find that our method provides speedups over the baseline for RMP construction of a full order of magnitude. We conduct several experiments on different benchmark problems to show the efficiency of our proposed algorithms Fast RMP and Fast-Approx WFOMC. |
| Researcher Affiliation | Collaboration | 1State Key Laboratory of Software Development Environment & Engineering Research Center of ACAT, Ministry of Education. Beihang University, China 2KU Leuven, Belgium 3Research Institute of Beihang University in Shenzhen, China 4CRRC Zhuzhou Institute, China & ETH Zurich, Switzerland 5Czech Technical University in Prague, Czech Republic |
| Pseudocode | Yes | Algorithm 1 Fast-RMP; Algorithm 2 Fast-Approx WFOMC |
| Open Source Code | No | The paper states: "We use Forclift4 as the WFOMC oracle, Quick Hull5 as the backend for the convex hull problem, and an interior point method [Boyd and Vandenberghe, 2004] to solve LPs. We follow van Bremen and Kuzelka [2020] and utilize Approx MC4 [Soos and Meel, 2019] as an approximate MC oracle." It lists URLs for Forclift and Quick Hull, but these are third-party tools, not the authors' own implementation code for the methods described in *this* paper. |
| Open Datasets | No | The paper uses |
| Dataset Splits | No | The paper does not explicitly specify training/validation/test dataset splits. It describes the MLN formulas and domain sizes used for experiments but no explicit splits. |
| Hardware Specification | Yes | All experiments are performed on a computer with an eightcore Intel i7 3.60GHz processor and 32 GB of RAM. |
| Software Dependencies | No | The paper mentions software like Forclift, Quick Hull, Approx MC4, and implies the use of a Python implementation for some aspects, but it does not provide specific version numbers for these software dependencies, nor for Python itself. For example, it lists "Forclift4" but the '4' is part of the name rather than a version number, and the URL for Forclift also doesn't specify a version. |
| Experiment Setup | Yes | The hyperparameters in our WFOMC approximation experiments are set to ε 0.8, δ 0.2 and τ 0.5, just as in the original paper. |