Understanding Regularized Spectral Clustering via Graph Conductance
Authors: Yilin Zhang, Karl Rohe
NeurIPS 2018 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | We provide simulations and data examples to illustrate these results. |
| Researcher Affiliation | Academia | Yilin Zhang Department of Statistics University of Wisconsin-Madison Madison, WI 53706 yilin.zhang@wisc.edu Karl Rohe Department of Statistics University of Wisconsin-Madison Madison, WI 53706 karl.rohe@wisc.edu |
| Pseudocode | No | The paper does not contain any pseudocode or clearly labeled algorithm blocks. |
| Open Source Code | No | The paper does not provide any explicit statements about releasing source code for the methodology described, nor does it include a direct link to a code repository. |
| Open Datasets | Yes | This section studies 37 example networks from http://snap.stanford.edu/data [14]. [14] Jure Leskovec and Andrej Krevl. SNAP Datasets: Stanford large network dataset collection. http://snap.stanford.edu/data, June 2014. |
| Dataset Splits | No | In this simulation, half of the edges are removed from the graph and placed into a testing-set . Refer to the remaining edges as the training-edges . While a train/test split is described, there is no explicit mention of a validation set or split. |
| Hardware Specification | No | The paper does not provide any specific details about the hardware (e.g., GPU/CPU models, memory) used for running the experiments. |
| Software Dependencies | Yes | All eigen-computations are performed with rARPACK [13, 18]. ... [18] Yixuan Qiu, Jiali Mei, and authors of the ARPACK library. See file AUTHORS for details. r ARPACK: Solvers for Large Scale Eigenvalue and SVD Problems, 2016. R package version 0.11-0. |
| Experiment Setup | Yes | Throughout all simulations, the regularization parameter τ is set to be the average degree of the graph. This is not optimized, but is instead a previously proposed heuristic [17]. As defined in Section 2 Equation 2.1, the partitions are constructed by scanning through the second eigenvector. ... Running times are from rARPACK computing two eigenvectors of D 1/2 τ AD 1/2 τ and D 1/2AD 1/2 using the default settings. |