115 citations · 212 across the 15 of their papers we have counts for
4 papers · 1 filter
Rethinking Large-scale Pre-ranking System: Entire-chain Cross-domain Models
Jinbo Song, Ruoran Huang, Xinyang Wang +9
Industrial systems such as recommender systems and online advertising, have been widely equipped with multi-stage architectures, which are divided into several cascaded modules, in…
HiNet: Novel Multi-Scenario & Multi-Task Learning with Hierarchical Information Extraction
Jie Zhou, Xianshuai Cao, Wenhao Li +4
Multi-scenario & multi-task learning has been widely applied to many recommendation systems in industrial applications, wherein an effective and practical approach is to carry out…
Feature Decomposition for Reducing Negative Transfer: A Novel Multi-task Learning Method for Recommender System
Jie Zhou, Qian Yu, Chuan Luo +1
In recent years, thanks to the rapid development of deep learning (DL), DL-based multi-task learning (MTL) has made significant progress, and it has been successfully applied to re…
Further Theoretical Study of Distribution Separation Method for Information Retrieval
Peng Zhang, Qian Yu, Yuexian Hou +3
Recently, a Distribution Separation Method (DSM) is proposed for relevant feedback in information retrieval, which aims to approximate the true relevance distribution by separating…