Open Problem: Improper Learning of Mixtures of Gaussians

Elad Hazan, Roi Livni

Research output: Contribution to journalConference articlepeer-review


We ask whether there exists an efficient unsupervised learning algorithm for mixture of Gaussians in the over-complete case (number of mixtures is larger than the dimension). The notion of learning is taken to be worst-case compression-based, to allow for improper learning.

Original languageEnglish
Pages (from-to)3399-3402
Number of pages4
JournalProceedings of Machine Learning Research
StatePublished - 2018
Externally publishedYes
Event31st Annual Conference on Learning Theory, COLT 2018 - Stockholm, Sweden
Duration: 6 Jul 20189 Jul 2018


Dive into the research topics of 'Open Problem: Improper Learning of Mixtures of Gaussians'. Together they form a unique fingerprint.

Cite this