A list of recent works in Fairness in Network Representation Learning

Fairness-aware Data Mining

Distillation of GANs with fairness constraints

Implementations of Fair-NeRV/Fair-t-NeRV

This Repository is for Kaggle NLP Challenge

This project Implements the paper “Causal Adversarial Perturbations for Individual Fairness and Robustness in Heterogeneous Data Spaces” using the Python language.

MANILA, a low-code framework for Quality-Based ML development

A model-based algorithm for the fair-capacitated clustering problem

This repository is for the research project: Is Meritocracy Just? (MERITJUST). Please cite my paper using the link below if you use any of its materials. Duong, K. Is meritocracy just? New evidence from Boolean analysis and Machine learning. J Comput Soc Sc (2024).

Asynchronous distributed pricing, is an algorithm to make a fairness between wireless network.

🗝An interactive piece on the different types of fairness.

Presentation for a brief talk at URI about ethics in data science

major ideas of the session "Fair Clustering" from the NeurIPS 2019 conference

A KTANE mod preventing some exploits in competitive play.

Exercise repository for Algorithmic Fairness, Accountability and Ethics (Spring 2022), IT University of Copenhagen

Python code for training fair logistic regression classifiers.

Repositório contendo o código da minha dissertação.

This project focuses on detecting and mitigating bias in tabular and image datasets. First, we present two algorithms that seek to correct dataset bias by dynamically reweighting the data points without changing the labels. Subsequently, we propose a novel approach to inferring bias from a given image dataset.

Some @scikit-learn compatible tools to address fairness issues in classification problems.