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..
Experimental Design on a Budget for Sparse Linear Models and Applications
Authors: Sathya Narayanan Ravi, Vamsi Ithapu, Sterling Johnson, Vikas Singh
ICML 2016 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | We perform a detailed set of experiments, on benchmarks and a large neuroimaging study, showing that the proposed models are effective in practice. |
| Researcher Affiliation | Academia | Sathya N. Ravi EMAIL Vamsi K. Ithapu EMAIL Sterling C. Johnson EMAIL Vikas Singh EMAIL University of Wisconsin Madison William S. Middleton Memorial Veterans Hospital |
| Pseudocode | Yes | Algorithm 1 Alternating Minimization Algorithm, Algorithm 2 Randomized coordinate descent algorithm for solving (12) |
| Open Source Code | Yes | The code is publicly available at https://github.com/sraviuwmadison/Expdesign_sparse. |
| Open Datasets | Yes | two standard LASSO datasets (prostate, (Tibshirani, 1996) and lars, (Efron et al., 2004)) and Alzheimer s Disease Neuroimaging Initiative (ADNI) (neuro). |
| Dataset Splits | No | The paper refers to 'full model' and 'reduced setup' comparisons, and mentions 'train' and 'test' data in the context of the Alzheimer's study, but does not provide specific train/validation/test split percentages or sample counts for any dataset. |
| Hardware Specification | Yes | A single workstation with 8 cores and 32GB RAM is used for experiments. |
| Software Dependencies | No | The paper does not provide specific software dependencies with version numbers. |
| Experiment Setup | Yes | We ran 1000 epochs of EDI, and 50 main iterations of ED-S (with 20 iterations for each of its subproblems). |