Fair Allocation of Items in Multiple Regions
Authors: Houyu Zhou, Tianze Wei, Biaoshuai Tao, Minming Li
AAAI 2024 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | On the negative side, we show NP-hardness and inapproximability results about the aforementioned fairness notions. On the positive side, we propose several algorithms to compute the partial allocations that satisfy envy-based notions and allocations that approximate the above fairness notions. |
| Researcher Affiliation | Academia | 1Department of Computer Science, City University of Hong Kong 2School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University {houyuzhou2-c, t.z.wei-8}@my.cityu.edu.hk, bstao@sjtu.edu.cn, minming.li@cityu.edu.hk |
| Pseudocode | Yes | Algorithm 1: About-To-Envy-Satisfied Algorithm |
| Open Source Code | No | The paper does not provide concrete access to source code for the methodology described. |
| Open Datasets | No | The paper is theoretical and does not use or reference any datasets, thus no access information for a publicly available dataset is provided. |
| Dataset Splits | No | The paper is theoretical and does not report on empirical experiments, therefore no dataset split information is provided. |
| Hardware Specification | No | The paper is theoretical and does not discuss any hardware used for computations or experiments. |
| Software Dependencies | No | The paper does not specify any software dependencies with version numbers. |
| Experiment Setup | No | The paper is theoretical and does not describe an experimental setup with hyperparameters or training settings. |