Breakthrough in 'distributed deep learning'
Monday, December 9, 2019 - 17:00
in Mathematics & Economics
Computer scientists, using a divide-and-conquer approach that leverages the power of compressed sensing, have shown they can train the equivalent of a 100 billion-parameter distributed deep learning network on a single machine in less than 35 hours for product search and similar extreme classification problems.