2 papers
cs.IR2023
Towards the Better Ranking Consistency: A Multi-task Learning Framework for Early Stage Ads Ranking
Xuewei Wang, Qiang Jin, Shengyu Huang +10
Dividing ads ranking system into retrieval, early, and final stages is a common practice in large scale ads recommendation to balance the efficiency and accuracy. The early stage r…
cs.LG2020
Fully-Corrective Gradient Boosting with Squared Hinge: Fast Learning Rates and Early Stopping
Jinshan Zeng, Min Zhang, Shao-Bo Lin
Boosting is a well-known method for improving the accuracy of weak learners in machine learning. However, its theoretical generalization guarantee is missing in literature. In this…