Ilias discusses the challenges of defining a median in high dimensions, particularly the impact of outliers on accuracy. He shares insights on a robust algorithm developed to estimate the mean even with a significant percentage of outliers present. By employing spectral methods, the approach focuses on identifying and removing only the most consequential outliers, ensuring computational efficiency while maintaining accuracy.
