Cris MooreTitle:Noisy Tensors and Machine Learning (tutorial)
Speaker: Cris Moore, Santa Fe Institute
Abstract: Someone gives you a tensor. You have a hunch that it is a noisy observation of an underlying tensor which is low rank. Depending on what kind of noise has been applied, can you recover the underlying matrix, at least approximately? Can you do this efficiently? And how much noise can you tolerate? And what does this have to do with statistical physics?
The second lecture will be about what tensors can tell us about computational complexity. We will see several ways - both direct and indirect - in which problems on tensors lie at the heart of lower bounds in complexity theory.
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
Additional Questions?
If you have additional questions, feel free to reach out to a maintainer / contributor on the contact page.
