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 Coakley et alK. L. Coakley, T. Snelleman, H. Hoos, and O. E. Gundersen, "The embrace of open science: An analysis of a decade of AI research and 56 800 conference papers," Under Review, 2026..
Multi-view Subspace Clustering on Topological Manifold
Authors: Shudong Huang, Hongjie Wu, Yazhou Ren, Ivor Tsang, Zenglin Xu, Wentao Feng, Jiancheng Lv
NeurIPS 2022 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Experimental results on several benchmark datasets illustrate the effectiveness of the proposed model, compared to the state-of-the-art competitors over the clustering performance. |
| Researcher Affiliation | Collaboration | 1College of Computer Science, Sichuan University, China 2School of Computer Science and Engineering, UESTC, China 3Centre for Frontier AI Research, A STAR, Singapore 4School of Computer Science and Technology, Harbin Institute of Technology Shenzhen, China |
| Pseudocode | Yes | Algorithm 1: Algorithm to solve Eq. (18) and Algorithm 2: The Algorithm for Eq. (5) |
| Open Source Code | Yes | Did you include the code, data, and instructions needed to reproduce the main experimental results (either in the supplemental material or as a URL)? [Yes] We provide them as a URL. |
| Open Datasets | Yes | The experiments are conducted on several benchmark datasets, namely, 3Sources, MSRC, 100Leaves, COIL-20, Caltech-7, Caltech-20, and MNIST. The detailed information of all datasets is given in Appendix A. ... We list the datasets and the URLs to download them. |
| Dataset Splits | Yes | Did you specify all the training details (e.g., data splits, hyperparameters, how they were chosen)? [Yes] The important details are provided in Section 4.2 and in the code. |
| Hardware Specification | Yes | All experiments are run on a workstation with Intel(R) Core(TM) i7-4770K CPU @ 3.50GHz and 32GB RAM, equipped with an NVIDIA GeForce RTX 2080 Ti GPU. |
| Software Dependencies | Yes | All codes are implemented in MATLAB 2021b. |
| Experiment Setup | Yes | Here we empirically search them in the range [0.1,0.5,1,5,10,50] for simplicity. ... In general, we could obtain a promising clustering performance by setting α = β = 10 in practical applications. |