Evaluating the statistical significance of biclusters
Authors: Jason D. Lee, Yuekai Sun, Jonathan E. Taylor
NeurIPS 2015 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Finally, we present experimental validation of the various tests and biclustering algorithms. |
| Researcher Affiliation | Academia | Jason D. Lee, Yuekai Sun, and Jonathan Taylor Institute of Computational and Mathematical Engineering Stanford University Stanford, CA 94305 |
| Pseudocode | Yes | Algorithm 1 Greedy search algorithm |
| Open Source Code | No | The paper does not contain any statements about releasing source code or links to a code repository. |
| Open Datasets | No | We generate data from the model (1.1) for various values of n and k. |
| Dataset Splits | No | The paper does not specify any training, validation, or test dataset splits. It mentions generating data from a model, implying synthetic data without standard splits. |
| Hardware Specification | No | The paper does not provide any details about the specific hardware used for running the experiments. |
| Software Dependencies | No | The paper does not specify any software dependencies with version numbers used for the experiments. |
| Experiment Setup | No | The paper mentions generating data for various values of n and k and calibrating tests at alpha = 0.1, but it lacks specific hyperparameters or detailed system-level training settings. |