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..
Copula Multi-label Learning
Authors: Weiwei Liu
NeurIPS 2019 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Theoretically, we show that our estimator is an unbiased and consistent estimator and follows asymptotically a normal distribution. Moreover, we bound the mean squared error of estimator. The experimental results from various domains validate the superiority of our proposed approach. |
| Researcher Affiliation | Academia | Weiwei Liu School of Computer Science, Wuhan University Wuhan, China 430072 EMAIL |
| Pseudocode | No | The paper describes the model and estimation procedures using mathematical equations and textual descriptions, but does not include explicit pseudocode or algorithm blocks. |
| Open Source Code | No | The paper mentions using the code provided by the respective authors for baseline methods but does not provide a statement or link for the open-sourcing of their own methodology's code. |
| Open Datasets | Yes | This section evaluates the performance of the proposed method on five real-world benchmark data sets with various domains: EMOTIONS (music), SCENE (image), MEDICAL (text), YEAST (biology) and ENRON (text). The statistics of these data sets are presented in the website1. 1http://mulan.sourceforge.net/datasets-mlc.html |
| Dataset Splits | Yes | We perform 3-fold cross-validation on each data set and report the mean and standard error of each evaluation measurement. |
| Hardware Specification | No | The paper does not provide specific hardware details (like GPU/CPU models, memory) used for running its experiments. |
| Software Dependencies | No | The paper does not provide specific ancillary software details with version numbers needed to replicate the experiment. |
| Experiment Setup | Yes | The bandwidth is set to h = 0.1 in the experiment. |