Parallel Algorithm for Non-Monotone DR-Submodular Maximization
Authors: Alina Ene, Huy Nguyen
ICML 2020 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | 6. Experimental Results We experimentally evaluate our parallel algorithm on instances of non-concave quadratic programming (NQP) and softmax extension of determinantal point processes (DPP) that were randomly generated similarly to previous work (Bian et al., 2017). |
| Researcher Affiliation | Academia | 1Department of Computer Science, Boston University 2Khoury College of Computer and Information Science, Northeastern University. |
| Pseudocode | Yes | Algorithm 1 Algorithm for max x [0,1]n : x 1 k f( x), where f is a non-negative DR-submodular function. |
| Open Source Code | Yes | The code used for generating the instances and evaluating the algorithms can be found in the supplement. |
| Open Datasets | No | The paper states 'We experimentally evaluate our parallel algorithm on instances of non-concave quadratic programming (NQP) and softmax extension of determinantal point processes (DPP) that were randomly generated similarly to previous work (Bian et al., 2017).' and describes their generation process, but does not provide specific access information (link, DOI, repository) for a publicly available dataset. |
| Dataset Splits | No | The paper evaluates its algorithm on 'instances' but does not specify training, validation, or test dataset splits or percentages. |
| Hardware Specification | Yes | We implemented the algorithms in C++ and ran the experiments on an iMac with a 3.3 GHz Intel Core i5 processor and 8 GB of memory. |
| Software Dependencies | No | The paper states 'We implemented the algorithms in C++' but does not specify version numbers for C++ or any other software dependencies. |
| Experiment Setup | Yes | We used error ϵ = 0.05 and budget k = 10 in all of the experiments. We implemented our algorithm with a more aggressive update of the thresholds on line 13: instead of the update v (1 ϵ)v, we performed the update v 0.75 v. |