General Tensor Spectral Co-clustering for Higher-Order Data
Authors: Tao Wu, Austin R. Benson, David F. Gleich
NeurIPS 2016 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | We use experiments on both synthetic and real-world problems to validate the effectiveness of our method. For the synthetic experiments, we devise a planted cluster model for tensors and show that GTSC has superior performance compared to other state-of-the-art clustering methods in recovering the planted clusters. In real-world tensor data experiments, we find that our GTSC framework identifies stop-words and semantically independent sets in n-gram tensors as well as worldwide and regional airlines and airports in a flight multiplex network. |
| Researcher Affiliation | Academia | Tao Wu Purdue University wu577@purdue.edu Austin R. Benson Stanford University arbenson@stanford.edu David F. Gleich Purdue University dgleich@purdue.edu |
| Pseudocode | No | The paper describes the algorithm using numbered steps within paragraphs, but it does not contain a structured pseudocode block or a clearly labeled algorithm section. |
| Open Source Code | Yes | Code and data for this paper are available at: https://github.com/wutao27/Gtensor SC |
| Open Datasets | Yes | Data were collected from http://openflights.org/data.html#route. English n-gram data were collected from http://www.ngrams.info/intro.asp and Chinese n-gram data were collected from https://books.google.com/ngrams. |
| Dataset Splits | No | The paper describes the generation of synthetic data and the real-world datasets used, but it does not specify explicit train/validation/test splits (e.g., percentages or sample counts) for reproducibility. |
| Hardware Specification | No | The paper does not provide specific hardware details (e.g., GPU/CPU models, memory) used for running its experiments. |
| Software Dependencies | No | The paper does not provide specific ancillary software details, such as library names with version numbers, used to implement and run the experiments. |
| Experiment Setup | Yes | For our experiments, we found that high values (e.g., 0.95) of α do not impede convergence. We use α = 0.8 for all our experiments. For all of our experiments, we set the teleportation probability α = 0.8 and the minimum cluster size for splitting min_size = 2. We set the target conductance φ = 0.3. |