Improved Communication Cost in Distributed PageRank Computation – A Theoretical Study
Authors: Siqiang Luo
ICML 2020 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | Improved Communication Cost in Distributed Page Rank Computation A Theoretical Study |
| Researcher Affiliation | Academia | 1Harvard University. Correspondence to: Siqiang Luo <siqiangluo@seas.harvard.edu>. |
| Pseudocode | Yes | Algorithm 1 Estimating Page Ranks based on Unit Task; Algorithm 2 Estimating Page Ranks based on Simple Unit Task; Algorithm 3 Estimating Page Ranks with Improved Bandwidth |
| Open Source Code | No | The paper does not provide any explicit statements or links indicating that open-source code for the described methodology is available. |
| Open Datasets | No | The paper is a theoretical study and does not describe experiments using specific datasets, nor does it provide information about dataset availability. It refers to a 'graph of n nodes' as a theoretical construct. |
| Dataset Splits | No | The paper is a theoretical study and does not mention dataset splits for training, validation, or testing, as it does not conduct empirical experiments. |
| Hardware Specification | No | The paper is a theoretical study and does not mention any specific hardware used for experiments. |
| Software Dependencies | No | The paper is a theoretical study and does not mention any specific software dependencies with version numbers. |
| Experiment Setup | No | The paper is a theoretical study and does not include details about an experimental setup, such as hyperparameters or system-level training settings, as it does not conduct empirical experiments. |