A Flexible Latent Space Model for Multilayer Networks
Authors: Xuefei Zhang, Songkai Xue, Ji Zhu
ICML 2020 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | The superior performance of the proposed model is demonstrated through simulation studies and applications to two real-world data examples. |
| Researcher Affiliation | Academia | 1Department of Statistics, University of Michigan, Ann Arbor, MI, USA. Correspondence to: Ji Zhu <jizhu@umich.edu>. |
| Pseudocode | Yes | Algorithm 1 Projected Gradient Descent Algorithm for Parameter Estimation |
| Open Source Code | No | The paper does not provide any specific links or explicit statements about the availability of source code for the described methodology. |
| Open Datasets | Yes | The Lazega Lawyers dataset records multiple connection re lationships in a Northeastern US corporate law firm (Lazega et al., 2001). ... Banerjee et al. (2013) provided multiple social networks in villages in rural southern Karnataka, India. |
| Dataset Splits | No | The paper specifies removing 20% entries for link prediction testing, but it does not provide explicit train/validation/test dataset splits needed to reproduce the model training (e.g., percentages or sample counts for validation sets for hyperparameter tuning). |
| Hardware Specification | No | The paper does not provide specific hardware details (e.g., exact GPU/CPU models, memory amounts) used for running its experiments. |
| Software Dependencies | No | The paper does not list specific software dependencies with version numbers (e.g., programming languages, libraries, or solvers with their versions). |
| Experiment Setup | Yes | We set n = 400, R = 100, and k = 2. ... initial estimates: U0, {α0 }r=1; step sizes ηu, ηα, ηλ; number of iterations T ... The step sizes ηα, ηλ are chosen to be small and fixed, and ηu is proportional to R −10 . |