Reviews: Extreme Classification in Log Memory using Count-Min Sketch: A Case Study of Amazon Search with 50M Products

This paper studies the task of extreme classification with a large amount of target categories. It developed a hashing-based algorithm, MACH. Then a classifier is trained and applied for each hash mapping, on the reduced problem with much smaller amount of target classes. The prediction results of the sub-classifiers are then combined to re-constructed the final output. The proposed methods are demonstrated to be both efficient and effective in multiple datasets.