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..
Optimal Weak to Strong Learning
Authors: Kasper Green Larsen, Martin Ritzert
NeurIPS 2022 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | Our work is purely theoretic (set within learning theory) and is thus not expected to impact society outside of the scientific community |
| Researcher Affiliation | Academia | Kasper Green Larsen Department of Computer Science Aarhus University Aarhus, Denmark EMAIL Martin Ritzert Department of Computer Science Aarhus University Aarhus, Denmark EMAIL |
| Pseudocode | Yes | Algorithm 1: Sub-Sample(A, B) Algorithm 2: Optimal weak-to-strong learner |
| Open Source Code | No | (a) Did you include the code, data, and instructions needed to reproduce the main experimental results (either in the supplemental material or as a URL)? [N/A] |
| Open Datasets | No | The paper is theoretical and does not describe using any dataset for training. The Ethics Review Checklist states 'N/A' for questions related to experiments and data. |
| Dataset Splits | No | The paper is theoretical and does not describe any experimental validation using dataset splits. The Ethics Review Checklist states 'N/A' for questions related to experiments and data. |
| Hardware Specification | No | The paper is purely theoretical and does not describe any experimental hardware. The Ethics Review Checklist states 'N/A' for 'total amount of compute and the type of resources used'. |
| Software Dependencies | No | The paper is purely theoretical and does not describe any software dependencies with specific version numbers for experimental reproducibility. The Ethics Review Checklist states 'N/A' for 'include the code'. |
| Experiment Setup | No | The paper is purely theoretical and does not describe an experimental setup with hyperparameters or training details. The Ethics Review Checklist states 'N/A' for 'specify all the training details'. |