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

NeurIPS 2019 Tharun MediniQixuan HuangYiqiu WangVijai MohanAnshumali Shrivastava

In the last decade, it has been shown that many hard AI tasks, especially in NLP, can be naturally modeled as extreme classification problems leading to improved precision. However, such models are prohibitively expensive to train due to the memory blow-up in the last layer... (read more)

PDF Abstract

Results from the Paper


  Submit results from this paper to get state-of-the-art GitHub badges and help the community compare results to other papers.

Methods used in the Paper