Stateful Strategic Regression
Authors: Keegan Harris, Hoda Heidari, Steven Z. Wu
NeurIPS 2021 | Venue PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Crucially, perhaps our most significant finding is that by considering the effects of multiple time-steps, the principal is significantly more effective at incentivizing the agent to accumulate effort in her desired direction (as demonstrated in Figure 1 for a stylized teacher-student example). |
| Researcher Affiliation | Academia | Keegan Harris School of Computer Science Carnegie Mellon University Pittsburgh, PA 15213 EMAIL Hoda Heidari School of Computer Science Carnegie Mellon University Pittsburgh, PA 15213 EMAIL Zhiwei Steven Wu School of Computer Science Carnegie Mellon University Pittsburgh, PA 15213 EMAIL |
| Pseudocode | Yes | Algorithm 1: Assessment Policy Recovery |
| Open Source Code | No | The paper does not provide any explicit statement or link indicating that source code for the described methodology is publicly available. |
| Open Datasets | No | The paper discusses a 'classroom example' as a stylized case study but does not refer to the use of a public or open dataset with access information (e.g., links, DOIs, or specific citations). |
| Dataset Splits | No | The paper does not provide details on training, validation, or test dataset splits. The work is theoretical with a stylized example, not an empirical study requiring data partitioning. |
| Hardware Specification | No | The paper does not specify any hardware details (e.g., GPU models, CPU types, or memory) used for running experiments or computations. |
| Software Dependencies | No | The paper does not provide specific version numbers for any software libraries, tools, or programming languages used in the research. |
| Experiment Setup | No | The paper does not include specific details about an experimental setup, such as hyperparameter values, optimization settings, or other configuration information typical for empirical studies. |