Adaptive Neural Ranking Framework: Toward Maximized Business Goal for Cascade Ranking Systems

no code implementations • 16 Oct 2023 • Yunli Wang, Zhiqiang Wang, Jian Yang, Shiyang Wen, Dongying Kong, Han Li, Kun Gai

Concretely, we employ multi-task learning to adaptively combine the optimization of relaxed and full targets, which refers to metrics Recall@m@k and OPA respectively.

Learning-To-Rank Multi-Task Learning +1

AMCAD: Adaptive Mixed-Curvature Representation based Advertisement Retrieval System

no code implementations • 28 Mar 2022 • Zhirong Xu, Shiyang Wen, Junshan Wang, Guojun Liu, Liang Wang, Zhi Yang, Lei Ding, Yan Zhang, Di Zhang, Jian Xu, Bo Zheng

Moreover, to deploy AMCAD in Taobao, one of the largest ecommerce platforms with hundreds of million users, we design an efficient two-layer online retrieval framework for the task of graph based advertisement retrieval.

Graph Embedding Information Retrieval +1

A bi-diffusion based layer-wise sampling method for deep learning in large graphs

no code implementations • 25 Sep 2019 • Yu He, Shiyang Wen, Wenjin Wu, Yan Zhang, Siran Yang, Yuan Wei, Di Zhang, Guojie Song, Wei Lin, Liang Wang, Bo Zheng

The Graph Convolutional Network (GCN) and its variants are powerful models for graph representation learning and have recently achieved great success on many graph-based applications.

Graph Representation Learning