RS3CIS: Robust Single-Step Spectral Clustering with Intrinsic Subspace
Authors: Yun Xiao, Pengzhen Ren, Zhihui Li, Xiaojiang Chen, Xin Wang, Dingyi Fang5482-5489
AAAI 2019 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | One synthetic dataset and six real benchmark datasets are used to verify the performance of the proposed method by performing clustering and projection experiments. Experimental results show that RS3CIS outperforms the related methods with respect to clustering quality, robustness and dimension reduction. |
| Researcher Affiliation | Academia | Yun Xiao,1 Pengzhen Ren,1 Zhihui Li,2 Xiaojiang Chen,1 Xin Wang,1,3 Dingyi Fang 1 1School of Information Science and Technology, Northwest University, Xi an 710127, P.R. China 2School of Computer Science and Engineering, University of New South Wales, Sydney, NSW 2052, Australia 3Department of Geomatics Engineering, University of Calgary, Calgary, AB T2N1N4, Canada |
| Pseudocode | Yes | Algorithm 1: Optimization of transformation matrix W in problem (10) |
| Open Source Code | No | The paper does not provide concrete access to source code for the methodology described. |
| Open Datasets | Yes | Among them, four image datasets: USPS1, Palm2, Ecoli (Athitsos and Sclaroff 2005) and Coil (Nene et al. 1996). Two biological datasets: Yeast (Asuncion and Newman 2007) comes from the UCI Machine Learning Repository, Wine is downloaded from (Zhong and Fukushima 2007). ... 1http://www-i6.informatik.rwth-aachen.de/keysers/usps.html 2http://www.escience.cn/people/fpnie/index.html |
| Dataset Splits | No | The paper does not provide specific dataset split information (exact percentages, sample counts, citations to predefined splits, or detailed splitting methodology) needed to reproduce the data partitioning for training or validation sets. |
| Hardware Specification | No | The paper does not provide specific hardware details (exact GPU/CPU models, processor types with speeds, memory amounts, or detailed computer specifications) used for running its experiments. |
| Software Dependencies | No | The paper does not provide specific ancillary software details (e.g., library or solver names with version numbers) needed to replicate the experiment. |
| Experiment Setup | Yes | we run them 100 times with random initializations, and report their average performance (Ave), standard deviation (std) and optimal clustering result (Best (min obj)). ... And the corresponding number of neighbor nodes is set to ten. In our method, K in parameter α is set to fifteen. ... The γ in our method RS3CIS is taken from {1e-6,1e-3,1,1e3,1e6}. |