Bias-Aware Curriculum Sampling For Fair Ranking

Shirin Seyedsalehi, Hai Son Le, Morteza Zihayat, Ebrahim Bagheri
January 2025

Abstract

This paper presents bias-aware curriculum sampling approaches for fair ranking, improving fairness in information retrieval systems through intelligent sampling strategies.

Type
Conference paper
Publication
Proceedings of the 48th International ACM SIGIR Conference on Research and Development in Information Retrieval

This work introduces bias-aware curriculum sampling for fair ranking systems.

Bias-Aware Sampling Curriculum Sampling Fair Ranking Information Retrieval Bias Mitigation
Hai Son Le
Hai Son Le
Master’s Student

Hai Son Le is a Master’s student in the Human-Centered Machine Intelligence Lab, working on research projects in machine learning and data science.

Morteza Zihayat
Morteza Zihayat
Principal Investigator

Dr. Morteza Zihayat is an Assistant Professor in the School of Information Technology Management at Toronto Metropolitan University and the Director of the Human-Centered Machine Intelligence Lab.