Distribution-free inference for regression: discrete, continuous, and in between
Authors: Yonghoon Lee, Rina Barber
NeurIPS 2021 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | Our main theoretical results show that there are two regimes. |
| Researcher Affiliation | Academia | Yonghoon Lee Department of Statistics University of Chicago Chicago, IL 60637 yhoony31@uchicago.edu, Rina Foygel Barber Department of Statistics University of Chicago Chicago, IL 60637 rina@uchicago.edu |
| Pseudocode | No | The paper describes the steps of its construction in Section 3, such as 'Step 1: estimate the effective support size', 'Step 2: estimate error at each repeated X value', and 'Step 3: construct the confidence interval'. While these are algorithmic steps, they are presented in prose with mathematical formulas rather than a formally labeled pseudocode or algorithm block. |
| Open Source Code | No | If you ran experiments... (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 conduct experiments with specific datasets, therefore it does not mention public access information for training data. The checklist explicitly states 'N/A' for experimental questions. |
| Dataset Splits | No | The paper is theoretical and does not report on experiments with data splits. The checklist explicitly states 'N/A' for experimental questions. |
| Hardware Specification | No | The paper is theoretical and does not conduct experiments requiring specific hardware. The checklist under 'If you ran experiments...' explicitly states '[N/A]' for questions related to compute resources. |
| Software Dependencies | No | The paper is theoretical and does not specify software dependencies with version numbers for experimental reproducibility. The checklist under 'If you ran experiments...' explicitly states '[N/A]' for related questions. |
| Experiment Setup | No | The paper is theoretical and does not detail an experimental setup with specific hyperparameters or training configurations. The checklist under 'If you ran experiments...' explicitly states '[N/A]' for related questions. |