Yong He

According to our database, Yong He authored at least 18 papers between 2019 and 2023.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2023

AntM²C: A Large Scale Dataset For Multi-Scenario Multi-Modal CTR Prediction.

Zhaoxin Huan, Ke Ding, Ang Li, Xiaolu Zhang, Xu Min, Yong He, Liang Zhang, Jun Zhou, Linjian Mo, Jinjie Gu, Zhongyi Liu, Wenliang Zhong, Guannan Zhang

CoRR, 2023

DCBT: A Simple But Effective Way for Unified Warm and Cold Recommendation.

Jieyu Yang, Liang Zhang, Yong He, Ke Ding, Zhaoxin Huan, Xiaolu Zhang, Linjian Mo

Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2023

Uncertainty-based Heterogeneous Privileged Knowledge Distillation for Recommendation System.

Ang Li, Jian Hu, Ke Ding, Xiaolu Zhang, Jun Zhou, Yong He, Xu Min

Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2023

SAMD: An Industrial Framework for Heterogeneous Multi-Scenario Recommendation.

Zhaoxin Huan, Ang Li, Xiaolu Zhang, Xu Min, Jieyu Yang, Yong He, Jun Zhou

Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

Global-Aware Model-Free Self-distillation for Recommendation System.

Ang Li, Jian Hu, Wei Lu, Ke Ding, Xiaolu Zhang, Jun Zhou, Yong He, Liang Zhang, Lihong Gu

Proceedings of the Database Systems for Advanced Applications, 2023

DAE: Distribution-Aware Embedding for Numerical Features in Click-Through Rate Prediction.

Bin Shen, Jingran Xu, Xu Min, Zeyu Ke, Yong He, Liang Zhang, Xin Dong, Linjian Mo

Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023

SeqGen: A Sequence Generator via User Side Information for Behavior Sparsity in Recommendation.

Xu Min, Xiaolu Zhang, Bin Shen, Shuhan Wang, Yong He, Changsheng Li, Jun Zhou

Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023

MI-DPG: Decomposable Parameter Generation Network Based on Mutual Information for Multi-Scenario Recommendation.

Wenzhuo Cheng, Ke Ding, Xin Dong, Yong He, Liang Zhang, Linjian Mo

Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023

2022

An Industrial Framework for Cold-Start Recommendation in Zero-Shot Scenarios.

Zhaoxin Huan, Gongduo Zhang, Xiaolu Zhang, Jun Zhou, Qintong Wu, Lihong Gu, Jinjie Gu, Yong He, Yue Zhu, Linjian Mo

Proceedings of the SIGIR '22: The 45th International ACM SIGIR Conference on Research and Development in Information Retrieval, Madrid, Spain, July 11, 2022

Mixture of Graph Enhanced Expert Networks for Multi-task Recommendation.

Binbin Hu, Bin Shen, Ruize Wu, Zhiqiang Zhang, Yuetian Cao, Yong He, Liang Zhang, Linjian Mo, Jun Zhou

Proceedings of the PRICAI 2022: Trends in Artificial Intelligence, 2022

Task Similarity Aware Meta Learning for Cold-Start Recommendation.

Jieyu Yang, Zhaoxin Huan, Yong He, Ke Ding, Liang Zhang, Xiaolu Zhang, Jun Zhou, Linjian Mo

Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022

MASR: A Model-Agnostic Sparse Routing Architecture for Arbitrary Order Feature Sharing in Multi-Task Learning.

Xin Dong, Ruize Wu, Chao Xiong, Hai Li, Lei Cheng, Yong He, Shiyou Qian, Jian Cao, Linjian Mo

Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022

GDOD: Effective Gradient Descent using Orthogonal Decomposition for Multi-Task Learning.

Xin Dong, Ruize Wu, Chao Xiong, Hai Li, Lei Cheng, Yong He, Shiyou Qian, Jian Cao, Linjian Mo

Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022

GFlow-FT: Pick a Child Network via Gradient Flow for Efficient Fine-Tuning in Recommendation Systems.

Ke Ding, Yong He, Xin Dong, Jieyu Yang, Liang Zhang, Ang Li, Xiaolu Zhang, Linjian Mo

Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022

CFS-MTL: A Causal Feature Selection Mechanism for Multi-task Learning via Pseudo-intervention.

Zhongde Chen, Ruize Wu, Cong Jiang, Honghui Li, Xin Dong, Can Long, Yong He, Lei Cheng, Linjian Mo

Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022

2021

Learning to Select Instance: Simultaneous Transfer Learning and Clustering.

Zhaoxin Huan, Yulong Wang, Yong He, Xiaolu Zhang, Chilin Fu, Weichang Wu, Jun Zhou, Ke Ding, Liang Zhang, Linjian Mo

Proceedings of the SIGIR '21: The 44th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2021

MSSM: A Multiple-level Sparse Sharing Model for Efficient Multi-Task Learning.

Ke Ding, Xin Dong, Yong He, Lei Cheng, Chilin Fu, Zhaoxin Huan, Hai Li, Tan Yan, Liang Zhang, Xiaolu Zhang, Linjian Mo

Proceedings of the SIGIR '21: The 44th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2021

2019

Robust feature screening for elliptical copula regression model.

Yong He, Liang Zhang, Jiadong Ji, Xinsheng Zhang

J. Multivar. Anal., 2019