Improving Nash Social Welfare Approximations
Authors: Jugal Garg, Peter McGlaughlin
IJCAI 2019 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | We present novel deļ¬nitions of fairness concepts in terms of market prices, and design a new scheme to round a market equilibrium into an integral allocation in a way that provides most of the fairness properties of an integral max NSW allocation. |
| Researcher Affiliation | Academia | Jugal Garg and Peter Mc Glaughlin University of Illinois at Urbana-Champaign {jugal, mcglghl2}@illinois.edu |
| Pseudocode | Yes | Algorithm 1: Rounding Algorithm |
| Open Source Code | No | The paper does not provide any statement or link indicating that the source code for the described methodology is publicly available. |
| Open Datasets | No | The paper focuses on theoretical algorithmic design and proofs, and does not conduct experiments on datasets that would require specifying public access or citation details. |
| Dataset Splits | No | The paper focuses on theoretical algorithmic design and proofs, and does not conduct experiments on datasets that would require specifying validation splits. |
| Hardware Specification | No | The paper describes theoretical algorithmic work and does not mention any specific hardware used for experiments. |
| Software Dependencies | No | The paper describes theoretical algorithmic work and does not mention any specific software dependencies with version numbers. |
| Experiment Setup | No | The paper focuses on theoretical algorithmic design and proofs, and does not describe an experimental setup with hyperparameters or training settings. |