A Local Non-Negative Pursuit Method for Intrinsic Manifold Structure Preservation
Authors: Dongdong Chen, Jian Cheng Lv, Zhang Yi
AAAI 2014 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Theoretical analysis and experimental results show that the proposed method achieves or outperforms the state-of-the-art results on various manifold learning problems. |
| Researcher Affiliation | Academia | Dongdong Chen and Jian Cheng Lv and Zhang Yi Machine Intelligence Laboratory College of Computer Science, Sichuan University Chengdu 610065, P. R. China |
| Pseudocode | Yes | Algorithm 1 Find Aopt: Local Non-negative Pursuit |
| Open Source Code | No | The paper does not provide any specific links or explicit statements about the availability of open-source code for the methodology described. |
| Open Datasets | No | The paper mentions datasets like 'COIL-20' and 'Extended Yale B', which are well-known, but it does not provide a direct URL, DOI, repository name, or a formal citation with author and year for accessing these datasets. |
| Dataset Splits | No | The paper discusses data usage for manifold embedding and clustering but does not specify training, validation, or test dataset splits (e.g., percentages or sample counts for each split). |
| Hardware Specification | Yes | All the experiments were carried out using MATLAB on a 2.2 GHz machine with 2.0GB RAM. |
| Software Dependencies | No | The paper mentions 'MATLAB' but does not provide a specific version number for the software used. |
| Experiment Setup | Yes | The paper specifies experimental parameters such as neighborhood size 'K = 2, 3, ..., 100' and 'λ = 60/100 for SMCE', which are settings used in the experiments. |