Lifted Inference Rules With Constraints
Authors: Happy Mittal, Anuj Mahajan, Vibhav G. Gogate, Parag Singla
NeurIPS 2015 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Experiments on benchmark MLNs for exact and sampling based inference demonstrate the effectiveness of our approach over several other existing techniques. |
| Researcher Affiliation | Academia | Happy Mittal, Anuj Mahajan Dept. of Comp. Sci. & Engg. I.I.T. Delhi, Hauz Khas New Delhi, 110016, India Vibhav Gogate Dept. of Comp. Sci. Univ. of Texas Dallas Richardson, TX 75080, USA Parag Singla Dept. of Comp. Sci. & Engg. I.I.T. Delhi, Hauz Khas New Delhi, 110016, India |
| Pseudocode | No | The paper refers to "Algorithm 2" and "our partitioning algorithm" and states "We refer the reader to the supplement section for a detailed description of our partitioning algorithm." but no pseudocode or algorithm block is present in the provided text. |
| Open Source Code | No | The paper mentions "Both our systems and GCFOVE are implemented in Java. PTP is implemented in C++." and provides links to "Alchemy-2:code.google.com/p-alchemy-2,GCFOVE: https:dtai.cs.kuleuven.be/software/gcfove". However, these links are for the systems they compared against, not for their own "Set In Eq" approach. No explicit statement or link for their own source code is provided. |
| Open Datasets | No | The paper mentions using "benchmark MLN domains" such as "Friends & Alchemy Smokes", "Web KB", and "IMDB", and provides a table with their details (Table 2). However, it does not provide concrete access information (e.g., links, DOIs, or specific repositories) for these datasets. |
| Dataset Splits | No | The paper does not explicitly provide information on training/validation/test dataset splits (e.g., percentages or sample counts) for its experiments. |
| Hardware Specification | Yes | The experiments on all the datasets except Web KB were carried on a machine with 2.20GHz Intel Core i3 CPU and 4GB RAM. Web KB is a much larger dataset and we ran the experiments on 2.20 GHz Xeon(R) E5-2660 v2 server with 10 cores and 128 GB RAM. |
| Software Dependencies | No | The paper states "Both our systems and GCFOVE are implemented in Java. PTP is implemented in C++." but does not provide specific version numbers for Java or C++, nor does it list any specific libraries with version numbers. |
| Experiment Setup | Yes | For approximate inference in both Normal and Set In Eq, we used the unbiased importance sampling scheme as described by Gogate & Domingos [11]. We collected a total of 1000 samples for each estimate and averaged the Z values. |