Equilibrium of Data Markets with Externality
Authors: Safwan Hossain, Yiling Chen
ICML 2024 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | We experimentally validate our theoretical insights on the effectiveness of transaction costs. While no publicly available dataset exists for data markets with prices and utilities, we take inspiration from AWS marketplace (a fixed price data market platform) we design a suite of synthetic experiments. |
| Researcher Affiliation | Academia | 1Harvard University, Cambridge, USA. Correspondence to: Safwan Hossain <shossain@g.harvard.edu>. |
| Pseudocode | Yes | Algorithm 1 Zooming algorithm for buyer i |
| Open Source Code | No | The paper mentions designing 'a suite of synthetic experiments' and uses 'a dataset derived from AWS Data Exchange' but does not provide any links to source code or explicit statements about its release. |
| Open Datasets | No | On a dataset derived from AWS Data Exchange. This is a derived dataset for synthetic experiments, and no public access details (link, DOI, specific citation to a public version) are provided for this specific dataset. |
| Dataset Splits | No | The paper does not provide specific training, validation, or test split percentages or sample counts for any dataset. |
| Hardware Specification | No | The paper does not provide specific details about the hardware used for running the experiments. |
| Software Dependencies | No | The paper does not provide specific software dependencies with version numbers. |
| Experiment Setup | Yes | We take the 10 different data categories from AWS, and instantiate several data sellers for each category (177 total sellers). For each category, we have several buyers (57 total), where each buyer has zero gain/externality for the sellers not in their category, with gains and externalities for their category sampled uniformly. They may purchase from up to 10% of the sellers in their category. |