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..
A Sharper Generalization Bound for Divide-and-Conquer Ridge Regression
Authors: Shusen Wang5305-5312
AAAI 2019 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | Since extensive empirical studies of the DC method have been conducted by (Zhang, Duchi, and Wainwright 2013; Wang, Gittens, and Mahoney 2018), we focus on the theory without conducting experiments. |
| Researcher Affiliation | Academia | Shusen Wang Department of Computer Science, Stevens Institute of Technology EMAIL |
| Pseudocode | No | The paper focuses on theoretical analysis and proofs and does not include any sections or figures explicitly labeled 'Pseudocode' or 'Algorithm'. |
| Open Source Code | No | The authors state, 'we focus on the theory without conducting experiments,' implying that no new code for the methodology described in this paper was developed or released. |
| Open Datasets | No | The paper states, 'we focus on the theory without conducting experiments,' indicating that no empirical evaluations were performed using a dataset. |
| Dataset Splits | No | The paper is theoretical and states, 'we focus on the theory without conducting experiments,' so no dataset splits for training, validation, or testing are provided. |
| Hardware Specification | No | The paper states, 'we focus on the theory without conducting experiments,' and thus does not provide any hardware specifications for experimental runs. |
| Software Dependencies | No | The paper explicitly states, 'we focus on the theory without conducting experiments,' and consequently does not list specific software dependencies with version numbers. |
| Experiment Setup | No | The paper explicitly states, 'we focus on the theory without conducting experiments,' and therefore does not describe any experimental setup details such as hyperparameters or training configurations. |