output
20172022
most citedA Semi-supervised Graph Attentive Network for Financial Fraud Detection

364 citations

14 papers

cs.IR20222 cited

Deep Unified Representation for Heterogeneous Recommendation

Chengqiang Lu, Mingyang Yin, Shuheng Shen +3

Recommendation system has been a widely studied task both in academia and industry. Previous works mainly focus on homogeneous recommendation and little progress has been made for…

cs.CR20201 cited

Secure Collaborative Training and Inference for XGBoost

Andrew Law, Chester Leung, Rishabh Poddar +6

In recent years, gradient boosted decision tree learning has proven to be an effective method of training robust models. Moreover, collaborative learning among multiple parties has…

cs.IR202012 cited

MTBRN: Multiplex Target-Behavior Relation Enhanced Network for Click-Through Rate Prediction

Yufei Feng, Fuyu Lv, Binbin Hu +5

Click-through rate (CTR) prediction is a critical task for many industrial systems, such as display advertising and recommender systems. Recently, modeling user behavior sequences…

cs.IR202062 cited

ATBRG: Adaptive Target-Behavior Relational Graph Network for Effective Recommendation

Yufei Feng, Binbin Hu, Fuyu Lv +3

Recommender system (RS) devotes to predicting user preference to a given item and has been widely deployed in most web-scale applications. Recently, knowledge graph (KG) attracts m…

cs.IR202082 cited

Open-Retrieval Conversational Question Answering

Chen Qu, Liu Yang, Cen Chen +3

Conversational search is one of the ultimate goals of information retrieval. Recent research approaches conversational search by simplified settings of response ranking and convers…

cs.LG20201 cited

A Riemannian Primal-dual Algorithm Based on Proximal Operator and its Application in Metric Learning

Shijun Wang, Baocheng Zhu, Lintao Ma +1

In this paper, we consider optimizing a smooth, convex, lower semicontinuous function in Riemannian space with constraints. To solve the problem, we first convert it to a dual prob…