High-Dimensional Robust Statistics with Ilias Diakonikolas - #351
The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence) - A podcast by Sam Charrington - Mondays
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Today we’re joined by Ilias Diakonikolas, faculty in the CS department at the University of Wisconsin-Madison, and author of the paper Distribution-Independent PAC Learning of Halfspaces with Massart Noise, recipient of the NeurIPS 2019 Outstanding Paper award. The paper is regarded as the first progress made around distribution-independent learning with noise since the 80s. In our conversation, we explore robustness in ML, problems with corrupt data in high-dimensional settings, and of course, the paper.
