Uncertain Decisions Facilitate Better Preference Learning
Authors: Cassidy Laidlaw, Stuart Russell
NeurIPS 2021 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | We give the first statistical analysis of IDT, providing conditions necessary to identify these preferences and characterizing the sample complexity the number of decisions that must be observed to learn the tradeoff the human is making to a desired precision. Our work also lacks computational analysis of algorithms for performing IDT. 3. 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] |
| Researcher Affiliation | Academia | Cassidy Laidlaw University of California, Berkeley cassidy_laidlaw@cs.berkeley.edu Stuart Russell University of California, Berkeley russell@cs.berkeley.edu |
| Pseudocode | No | No pseudocode or clearly labeled algorithm blocks were found in the paper. |
| Open Source Code | No | 3. 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 | No mention of a training dataset or its public availability was found, as the paper is theoretical and does not report experimental results with data. |
| Dataset Splits | No | No information regarding validation dataset splits was found, as the paper is theoretical and does not report experimental results. |
| Hardware Specification | No | No specific hardware details used for running experiments were provided, as the paper is theoretical and does not report empirical results from experiments. |
| Software Dependencies | No | No specific ancillary software details with version numbers were provided, as the paper is theoretical and does not report empirical results from experiments. |
| Experiment Setup | No | No specific experimental setup details, such as hyperparameter values or training configurations, were provided, as the paper is theoretical and does not report empirical results from experiments. |