Abstract
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 language | English |
|---|---|
| Pages (from-to) | 3399-3402 |
| Number of pages | 4 |
| Journal | Proceedings of Machine Learning Research |
| Volume | 75 |
| State | Published - 2018 |
| Externally published | Yes |
| Event | 31st Annual Conference on Learning Theory, COLT 2018 - Stockholm, Sweden Duration: 6 Jul 2018 → 9 Jul 2018 |
All Science Journal Classification (ASJC) codes
- Artificial Intelligence
- Software
- Control and Systems Engineering
- Statistics and Probability