https://www.sciencedaily.com/releases/2019/12/191209161341.htm

Using a divide-and-conquer approach that leverages the power of compressed sensing, computer scientists from Rice University and Amazon have shown they can slash the amount of time and computational resources it takes to train computers for product search and similar "extreme classification problems" like speech translation and answering general questions.

The research will be presented this week at the 2019 Conference on Neural Information Processing Systems (NeurIPS 2019) in Vancouver. The results include tests performed in 2018 when lead researcher Anshumali Shrivastava and lead author Tharun Medini, both of Rice, were visiting Amazon Search in Palo Alto, California.