Deep Learning breakthrough made by Rice University scientists

In particular, the more potential inputs you have to an algorithm, the more out of control your scaling problem gets when analyzing its problem space. This is where MACH, a research project authored by Rice University's Tharun Medini and Anshumali Shrivastava, comes in. MACH is an acronym for Merged Average Classifiers via Hashing, and according to lead researcher Shrivastava, "[its] training times are about 7-10 times faster, and... memory footprints are 2-4 times smaller" than those of previous large-scale deep learning techniques. In describing the scale of extreme classification problems, Medini refers to online shopping search queries, noting that "there are easily more than 100 million products online." This is, if anything, conservative--one data company claimed Amazon US alone sold 606 million separate products, with the entire company offering more than three billion products worldwide.