History Repeats Itself: A Baseline for Temporal Knowledge Graph Forecasting
Abstract
When dividing items among agents, two of the most widely studied fairness notions are envy-freeness and proportionality. We consider a setting where m chores are allocated to n agents and the disutility of each chore for each agent is drawn from a probability distribution. We show that an envy-free allocation exists with high probability provided that m >= 2n, and moreover, m must be at least n+Theta(n) in order for the existence to hold. On the other hand, we prove that a proportional allocation is likely to exist as long as m = omega(1), and this threshold is asymptotically tight. Our results reveal a clear contrast with the allocation of goods, where a larger number of items is necessary to ensure existence for both notions.
Cite
Text
Gastinger et al. "History Repeats Itself: A Baseline for Temporal Knowledge Graph Forecasting." International Joint Conference on Artificial Intelligence, 2024. doi:10.24963/ijcai.2024/444Markdown
[Gastinger et al. "History Repeats Itself: A Baseline for Temporal Knowledge Graph Forecasting." International Joint Conference on Artificial Intelligence, 2024.](https://mlanthology.org/ijcai/2024/gastinger2024ijcai-history/) doi:10.24963/ijcai.2024/444BibTeX
@inproceedings{gastinger2024ijcai-history,
title = {{History Repeats Itself: A Baseline for Temporal Knowledge Graph Forecasting}},
author = {Gastinger, Julia and Meilicke, Christian and Errica, Federico and Sztyler, Timo and Schülke, Anett and Stuckenschmidt, Heiner},
booktitle = {International Joint Conference on Artificial Intelligence},
year = {2024},
pages = {4016-4024},
doi = {10.24963/ijcai.2024/444},
url = {https://mlanthology.org/ijcai/2024/gastinger2024ijcai-history/}
}