An overview of quantum-inspired classical sampling
This is an adaptation of a talk I gave at Microsoft Research in November 2018.
I exposit the $\ell^2$ sampling techniques I use in my recommendation systems work and its follow-ups in dequantized machine learning. The core ideas are super simple. This goal of this blog post is to break down these ideas into intuition relevant for quantum researchers and create more understanding of this machine learning paradigm.