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 [1].
Multiclass versus Binary Differentially Private PAC Learning
Authors: Satchit Sivakumar, Mark Bun, Marco Gaboardi
NeurIPS 2021 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | Our focus is on theoretical questions aimed at uncovering general principles about when private learning is feasible. |
| Researcher Affiliation | Academia | Mark Bun Department of Computer Science Boston University Boston, MA 02215 EMAIL Marco Gaboardi Department of Computer Science Boston University Boston, MA 02215 EMAIL Satchit Sivakumar Department of Computer Science Boston University Boston, MA 02215 EMAIL |
| Pseudocode | No | The paper includes Figure 1 which is a diagram illustrating the algorithm, but it does not provide structured pseudocode or an algorithm block formatted like code. |
| Open Source Code | No | The paper does not provide any concrete access to source code for the methodology described. |
| Open Datasets | No | The paper is theoretical and does not conduct empirical studies with datasets, therefore no training data is used or mentioned as publicly available. |
| Dataset Splits | No | The paper is theoretical and does not describe experiments, therefore no dataset splits for training, validation, or testing are provided. |
| Hardware Specification | No | The paper is theoretical and does not describe any experimental setup or hardware used for computation. |
| Software Dependencies | No | The paper is theoretical and does not mention any specific software dependencies or versions. |
| Experiment Setup | No | The paper is theoretical and does not include any experimental setup details such as hyperparameters or training configurations. |