Search Results for author: Guodong Cao

Found 4 papers, 0 papers with code

CSPM: A Contrastive Spatiotemporal Preference Model for CTR Prediction in On-Demand Food Delivery Services

no code implementations10 Aug 2023 Guyu Jiang, Xiaoyun Li, Rongrong Jing, Ruoqi Zhao, Xingliang Ni, Guodong Cao, Ning Hu

Click-through rate (CTR) prediction is a crucial task in the context of an online on-demand food delivery (OFD) platform for precisely estimating the probability of a user clicking on food items.

Click-Through Rate Prediction Contrastive Learning +1

Spatiotemporal-Enhanced Network for Click-Through Rate Prediction in Location-based Services

no code implementations20 Sep 2022 Shaochuan Lin, Yicong Yu, Xiyu Ji, Taotao Zhou, Hengxu He, Zisen Sang, Jia Jia, Guodong Cao, Ning Hu

In Location-Based Services(LBS), user behavior naturally has a strong dependence on the spatiotemporal information, i. e., in different geographical locations and at different times, user click behavior will change significantly.

Click-Through Rate Prediction

Vanilla Feature Distillation for Improving the Accuracy-Robustness Trade-Off in Adversarial Training

no code implementations5 Jun 2022 Guodong Cao, Zhibo Wang, Xiaowei Dong, Zhifei Zhang, Hengchang Guo, Zhan Qin, Kui Ren

However, most existing works are still trapped in the dilemma between higher accuracy and stronger robustness since they tend to fit a model towards robust features (not easily tampered with by adversaries) while ignoring those non-robust but highly predictive features.

Knowledge Distillation

Context-aware Heterogeneous Graph Attention Network for User Behavior Prediction in Local Consumer Service Platform

no code implementations24 Jun 2021 Peiyuan Zhu, XiaoFeng Wang, Zisen Sang, Aiquan Yuan, Guodong Cao

Hence, in this paper, we propose a context-aware heterogeneous graph attention network (CHGAT) to dynamically generate the representation of the user and to estimate the probability for future behavior.

Graph Attention

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