Submodular Cost Submodular Cover with an Approximate Oracle
Authors: Victoria Crawford, Alan Kuhnle, My Thai
ICML 2019 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | In this section, we compute the approximation ratios stated in Theorems 1 and 2 on instances of the Influence Threshold problem (IT), a special case of SCSC. We use the nonsubmodular approximate reachability oracle that has been proposed by Cohen et al. (2014). |
| Researcher Affiliation | Academia | 1Department of Computer and Information Science and Engineering, University of Florida, Gainesville, Florida, United States 2Department of Computer Science, Florida State University, Tallahassee, Florida, United States. |
| Pseudocode | Yes | Algorithm 1 greedy(F, c, τ) Input:A value oracle to F : 2S R 0, a value oracle to c : 2S R 0, and τ. Fτ = min{F, τ} A = while F(A) < τ do u = argmaxx S\A Fτ(A, x)/c(x) A = A {u} end while return A |
| Open Source Code | No | The paper does not provide concrete access to source code (specific repository link, explicit code release statement, or code in supplementary materials) for the methodology described. |
| Open Datasets | Yes | We use two real social networks: the Facebook ego network (Leskovec & Mcauley, 2012), and the Ar Xi V General Relativity collaboration network (Leskovec et al., 2007), which we refer to as Gr Qc. |
| Dataset Splits | No | The paper does not provide specific dataset split information (exact percentages, sample counts, citations to predefined splits, or detailed splitting methodology) needed to reproduce the data partitioning. |
| Hardware Specification | No | The paper does not provide specific hardware details (exact GPU/CPU models, processor types with speeds, memory amounts, or detailed computer specifications) used for running its experiments. |
| Software Dependencies | No | The paper does not provide specific ancillary software details (e.g., library or solver names with version numbers like Python 3.8, CPLEX 12.4) needed to replicate the experiment. |
| Experiment Setup | No | The paper has an "Experimental Setup" section but it lacks specific hyperparameter values, detailed training configurations, or system-level settings, often deferring them to an appendix not provided in the main text. |