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..
Multi-way Interacting Regression via Factorization Machines
Authors: Mikhail Yurochkin, XuanLong Nguyen, nikolaos Vasiloglou
NeurIPS 2017 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Our method is evaluated with extensive experiments on simulated data and demonstrated to be able to identify meaningful interactions in applications in genetics and retail demand forecasting. |
| Researcher Affiliation | Collaboration | Mikhail Yurochkin Department of Statistics University of Michigan EMAIL Xuan Long Nguyen Department of Statistics University of Michigan EMAIL Nikolaos Vasiloglou Logic Blox EMAIL |
| Pseudocode | No | The paper mentions 'MCMC sampler (details of the sampler are in the Supplement)' but does not include pseudocode or algorithm blocks in the main body. |
| Open Source Code | Yes | Code is available at https://github.com/moonfolk/Mi FM. |
| Open Datasets | Yes | Our analysis of the epistasis is based on the data from Himmelstein et al. (2011). |
| Dataset Splits | No | The paper mentions 'Root Mean Squared Error on the held out data' and 'Prediction Accuracy on the Held-out Samples' but does not provide specific percentages, sample counts, or explicit splitting methodology for training/validation/test sets. |
| Hardware Specification | No | The paper does not provide specific hardware details (e.g., GPU/CPU models, memory) used for running its experiments. |
| Software Dependencies | No | The paper does not provide specific ancillary software details with version numbers (e.g., library or solver names with version numbers like Python 3.8, CPLEX 12.4) needed to replicate the experiment. |
| Experiment Setup | Yes | We will compare Mi FM1 and Mi FM0, both ο¬tted with K = 12 and J = 150 |