📢 New preprint! “When majority rules, minority loses: bias amplification of gradient descent” We often blame biased data but training also amplifies biases. Our paper explores how ML algorithms favor stereotypes at the expense of minority groups. ➡️ arxiv.org/abs/2505.13122 (1/3)

When majority rules, minority loses: bias amplification of gradient descent

Despite growing empirical evidence of bias amplification in machine learning, its theoretical foundations remain poorly understood. We develop a formal framework for majority-minority learning tasks, ...

arxiv.org

📣Job altertS in Toulouse (Maths department) 📣 There are multiple jobs offers from Master internships to Assistant professor in the mathematics of data science, optimization, statistical fairness and robustness. I will try to regroup them in this thread 🧵