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..
Conformalized Multiple Testing after Data-dependent Selection
Authors: Xiaoning Wang, Yuyang Huo, Liuhua Peng, Changliang Zou
NeurIPS 2024 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Furthermore, we conduct numerical studies to showcase the effectiveness and validity of our procedures across various scenarios. |
| Researcher Affiliation | Academia | 1School of Statistics and Data Sciences, LPMC, KLMDASR and LEBPS, Nankai University, Tianjin, China 2School of Mathematics and Statistics, The University of Melbourne, Melbourne, Australia |
| Pseudocode | Yes | Algorithm 1 Selective conformal p-value with BH procedure (SCPV) |
| Open Source Code | Yes | We provide the data and code in the supplemental materials, including instructions in the zip file. |
| Open Datasets | Yes | Abalone[37]: contains easily obtainable measurements of abalone. The task is to predict the age of abalone from physical measurements. |
| Dataset Splits | No | The paper mentions a 'labeled/holdout data set Dc' and an 'unlabelled/test set Du', and their sizes, but does not explicitly specify a separate validation dataset split with proportions. |
| Hardware Specification | Yes | All the experiments were conducted on AMD Ryzen 7 5800H with Radeon Graphics processor with 16 Gb memory at a Lenovo personal computer and the R platform with version 4.2.1. |
| Software Dependencies | Yes | All the experiments were conducted on AMD Ryzen 7 5800H with Radeon Graphics processor with 16 Gb memory at a Lenovo personal computer and the R platform with version 4.2.1. |
| Experiment Setup | Yes | We fix the labeled data size n = 1, 200 and the unlabeled data size m = 1, 200. We fit the regression models หยต( ) on an additional labeled set with size 1, 200 using the random forest algorithm, implemented by R package random Forest with default parameters. |