Notice: The reproducibility variables underlying each score are classified using an automated LLM-based pipeline, validated against a manually labeled dataset. LLM-based classification introduces uncertainty and potential bias; scores should be interpreted as estimates. Full accuracy metrics and methodology are described in [1].
Spectral Modification of Graphs for Improved Spectral Clustering
Authors: Ioannis Koutis, Huong Le
NeurIPS 2019 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | We provide a MATLAB implentation. We plan to provide a Python implementation in the near future. The submitted code and all future updates can be found in: https://github.com/ikoutis/spectral-modification. We performed experiments with four graphs (Blog Catalog, PPI, Wikipedia, Flickr) used as a benchmark in the recent literature [20, 22]. We compare against Net MF [22] as it has previously reported an improvement over Deep Walk [20] and other competing methods. |
| Researcher Affiliation | Academia | Ioannis Koutis Department of Computer Science New Jersey Institute of Technology Newark, NJ 07102 EMAIL; Huong Le Department of Computer Science New Jersey Institute of Technology Newark, NJ 07102 EMAIL |
| Pseudocode | Yes | 1: procedure ENERGY_TD(G, k) ... 9: return {T1, . . . , Tk} |
| Open Source Code | Yes | The submitted code and all future updates can be found in: https://github.com/ikoutis/spectral-modification |
| Open Datasets | Yes | We performed experiments with four graphs (Blog Catalog, PPI, Wikipedia, Flickr) used as a benchmark in the recent literature [20, 22]. |
| Dataset Splits | Yes | Figure 4: Micro-F1 scores in 10x cross-validation using LIBLINEAR [10]. |
| Hardware Specification | No | The paper mentions that "one eigenvector can be computed in mere seconds on standard hardware" but does not provide specific details (e.g., CPU, GPU models, memory) about the hardware used for their experiments. |
| Software Dependencies | No | The paper states "We provide a MATLAB implentation." and mentions using "LIBLINEAR [10]" and comparing against "Net MF [22]". However, it does not specify version numbers for MATLAB or any other software components used in their implementation. |
| Experiment Setup | Yes | Parameter Settings: For all our experiments we set k = 3, df = 1/2, and α = 1 in ENERGY_TD. |