4 papers
A Comprehensive Evaluation of the Sensitivity of Density-Ratio Estimation Based Fairness Measurement in Regression
Abdalwahab Almajed, Maryam Tabar, Peyman Najafirad
The prevalence of algorithmic bias in Machine Learning (ML)-driven approaches has inspired growing research on measuring and mitigating bias in the ML domain. Accordingly, prior re…
Machine Learning Fairness in House Price Prediction: A Case Study of America's Expanding Metropolises
Abdalwahab Almajed, Maryam Tabar, Peyman Najafirad
As a basic human need, housing plays a key role in enhancing health, well-being, and educational outcome in society, and the housing market is a major factor for promoting quality…
Improving LLM Reasoning with Multi-Agent Tree-of-Thought Validator Agent
Fatemeh Haji, Mazal Bethany, Maryam Tabar +3
Multi-agent strategies have emerged as a promising approach to enhance the reasoning abilities of Large Language Models (LLMs) by assigning specialized roles in the problem-solving…
On the Consistency of Fairness Measurement Methods for Regression Tasks
Abdalwahab Almajed, Maryam Tabar, Peyman Najafirad
With growing applications of Machine Learning (ML) techniques in the real world, it is highly important to ensure that these models work in an equitable manner. One main step in en…