Excited to present at #NeurIPS2024 our work on robust mixture learning!
How hard is mixture learning when (a lot of) outliers are present? We show that it's easier than it seems!
Join us at the poster session (Wed, 16:30 PT, West Ballroom A-D #5710).
How hard is mixture learning when (a lot of) outliers are present? We show that it's easier than it seems!
Join us at the poster session (Wed, 16:30 PT, West Ballroom A-D #5710).
Comments
However, when the fraction of outliers becomes larger than the smallest component, prior methods suffer both in recovery error and list size.
We propose a reduction from the robust mixture learning problem to a well-studied list-decodable mean estimation problem.
link: https://arxiv.org/abs/2407.15792
Joint with @raresbuhai.bsky.social, Stefan Tiegel, Alex Wolters, Gleb Novikov, @amartyasanyal.bsky.social, David Steurer, and Fanny Yang.