WSDM

A light-weight mini-batch creation technique that offers provably accurate in-batch negative samples for training retrieval models. This allows training with larger mini-batches offering significantly faster convergence and higher accuracies than existing negative sampling techniques.

This paper introduces a new learning paradigm called eXtreme Regression (XR) whose objective is to accurately predict the numerical degrees of relevance of an extremely large number of labels to a data point. XR can provide elegant solutions to many large-scale ranking and recommendation applications including Dynamic Search Advertising (DSA).