Course Materials

Reading Material

• Algorithmic fair allocation of indivisible items: a survey and new questions https://dl.acm.org/doi/abs/10.1145/3572885.3572887 (read before the class on September 13, 2024)

• Amanatidis, Georgios, et al. Fair division of indivisible goods: Recent progress and open questions. Artificial Intelligence, 2023. (read before the class on September 20, 2024)

• Barman, S., & Krishnamurthy, S. K. Approximation algorithms for maximin fair division. ACM Transactions on Economics and Computation (TEAC), 2020. (read before the class on September 20, 2024)

• Biswas and Barman. Fair Division under Cardinality Constraints. In Proceedings of the 27th International Joint Conference on Artificial Intelligence (IJCAI), 2018. (read before the class on September 20, 2024)

• Book: https://fairmlbook.org/ Chapters 3 and 4 (read before the class on September 27, 2024)

• Case Study: https://www.propublica.org/article/machine-bias-risk-assessments-in-criminal-sentencing (read before the class on September 27, 2024)

• Fairness in Recommendation: Foundations, Methods and Applications https://dl.acm.org/doi/abs/10.1145/3610302 (read before the class on October 4, 2024)