In this paper, we propose an efficient algorithm to accelerate computing the TT decomposition with the Alternating Least Squares (ALS) algorithm relying on exact leverage scores sampling.

We revisit this scenario as an experimental case study in Section 6.

Second, generalization--what specific aspects of the transformer architecture are responsible for their effective learning?

Large language models(LLMs) have sparked a new wave of exciting AI applications. Hosting these models at scale requires significant memory resources.