Infinite Plaid Models for Infinite Bi-Clustering

Authors: Katsuhiko Ishiguro, Issei Sato, Masahiro Nakano, Akisato Kimura, Naonori Ueda

AAAI 2016 | Conference PDF | Archive PDF | Plain Text | 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.