8 citations · 8 across the 6 of their papers we have counts for
5 papers · 1 filter
Fair Dataset Distillation via Cross-Group Barycenter Alignment
Mohammad Hossein Moslemi, Nima Hosseini Dashtbayaz, Zhimin Mei +2
Dataset Distillation aims to compress a large dataset into a small synthetic one while maintaining predictive performance. We show that as different demographic groups exhibit dist…
Reducing Biases in Record Matching Through Scores Calibration
Mohammad Hossein Moslemi, Mostafa Milani
Record matching models typically output a real-valued matching score that is later consumed through thresholding, ranking, or human review. While fairness in record matching has mo…
Evaluating Blocking Biases in Entity Matching
Mohammad Hossein Moslemi, Harini Balamurugan, Mostafa Milani
Entity Matching (EM) is crucial for identifying equivalent data entities across different sources, a task that becomes increasingly challenging with the growth and heterogeneity of…
Threshold-Independent Fair Matching through Score Calibration
Mohammad Hossein Moslemi, Mostafa Milani
Entity Matching (EM) is a critical task in numerous fields, such as healthcare, finance, and public administration, as it identifies records that refer to the same entity within or…
OTClean: Data Cleaning for Conditional Independence Violations using Optimal Transport
Alireza Pirhadi, Mohammad Hossein Moslemi, Alexander Cloninger +2
Ensuring Conditional Independence (CI) constraints is pivotal for the development of fair and trustworthy machine learning models. In this paper, we introduce \sys, a framework tha…