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 [1].
Infinite Plaid Models for Infinite Bi-Clustering
Authors: Katsuhiko Ishiguro, Issei Sato, Masahiro Nakano, Akisato Kimura, Naonori Ueda
AAAI 2016 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Experiments quantitatively and qualitatively verify the usefulness of the proposed model. The results reveal that our model can offer more precise and in-depth analysis of sub-matrices. |
| Researcher Affiliation | Collaboration | Katsuhiko Ishiguro, Issei Sato,* Masahiro Nakano, Akisato Kimura, Naonori Ueda NTT Communication Science Laboratories, Kyoto, Japan *The University of Tokyo, Tokyo, Japan |
| Pseudocode | No | The paper describes mathematical generative processes and inference steps but does not include a dedicated pseudocode block or algorithm listing. |
| Open Source Code | Yes | A supplemental material and information for a MATLAB demo program package can be found at: http://www.kecl.ntt.co.jp/as/members/ishiguro/index.html |
| Open Datasets | Yes | The Enron E-mail dataset is a collection of E-mail transactions in the Enron Corporation (Klimt and Yang 2004). |
| Dataset Splits | No | The paper mentions synthetic and real-world datasets but does not provide specific details on training, validation, or test splits (e.g., percentages, sample counts, or explicit split files). |
| Hardware Specification | No | The paper does not provide any specific details regarding the hardware (e.g., CPU, GPU models, memory) used for running the experiments. |
| Software Dependencies | No | The paper mentions a "MATLAB demo program package" but does not specify exact version numbers for MATLAB itself or any specific libraries/toolboxes used within it. |
| Experiment Setup | No | The paper states "All other hyperparameters of two models are inferred via MCMC inferences" but does not provide specific fixed hyperparameter values (e.g., learning rate, batch size, number of epochs) or other detailed training configurations. |