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..
Constrained NMF-Based Multi-View Clustering on Unmapped Data
Authors: Xianchao Zhang, Linlin Zong, Xinyue Liu, Hong Yu
AAAI 2015 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Experimental results show that, with a small number of constraints, the proposed algorithm gets good performance on unmapped data, and outperforms existing algorithms on partially mapped data and completely mapped data. |
| Researcher Affiliation | Academia | Xianchao Zhang, Linlin Zong, Xinyue Liu, Hong Yu School of Software Dalian University of Technology, Dalian 116620, China EMAIL, EMAIL, EMAIL, EMAIL |
| Pseudocode | Yes | Algorithm 1: CMVNMF algorithm |
| Open Source Code | No | The paper does not provide any statement or link indicating the availability of open-source code for the described methodology. |
| Open Datasets | Yes | Datasets We use three benchmark datasets, UCI Handwritten Digit1, Reuters2 and Webkb3 to investigate the impact of inter-view constraints on CMVNMF. UCI Handwritten consists of handwritten digits (0-9). ... 1http://archive.ics.uci.edu/ml/datasets/Multiple+Features 2http://membres-liglab.imag.fr/grimal/data.html 3http://www.cs.cmu.edu/afs/cs.cmu.edu/project/theo20/www/data/ |
| Dataset Splits | No | The paper describes datasets and how they were made unmapped (randomly selecting 95% samples and permuting), but it does not specify explicit training, validation, or test splits by percentage or sample count, nor does it mention cross-validation. |
| Hardware Specification | No | The paper does not provide any specific details about the hardware used to run the experiments. |
| Software Dependencies | No | The paper does not provide specific version numbers for any software dependencies used in the experiments. |
| Experiment Setup | Yes | We normalize the dataset in each view at ο¬rst. ... We initialize the algorithm by the result of a basic clustering method, e.g. k-means, in each view. ... We set Ξ² = 1 in all experiments. |