Jie Zhang

According to our database, Jie Zhang authored at least 20 papers between 2016 and 2025.

Collaborative distances:

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

2025

Efficient Long Context Fine-tuning with Chunk Flow.

Xiulong Yuan, Hongtao Xu, Wenting Shen, Ang Wang, Xiafei Qiu, Jie Zhang, Yuqiong Liu, Bowen Yu, Junyang Lin, Mingzhen Li, Weile Jia, Yong Li, Wei Lin

CoRR, March, 2025

Contextual Generative Auction with Permutation-level Externalities for Online Advertising.

Ruitao Zhu, Yangsu Liu, Dagui Chen, Zhenjia Ma, Chufeng Shi, Zhenzhe Zheng, Jie Zhang, Jian Xu, Bo Zheng, Fan Wu

Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining, V.1, 2025

2024

Unlearning during Learning: An Efficient Federated Machine Unlearning Method.

Hanlin Gu, Gongxi Zhu, Jie Zhang, Xinyuan Zhao, Yuxing Han, Lixin Fan, Qiang Yang

Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence, 2024

2023

OAG: Linking Entities Across Large-Scale Heterogeneous Knowledge Graphs.

Fanjin Zhang, Xiao Liu, Jie Tang, Yuxiao Dong, Peiran Yao, Jie Zhang, Xiaotao Gu, Yan Wang, Evgeny Kharlamov, Bin Shao, Rui Li, Kuansan Wang

IEEE Trans. Knowl. Data Eng., September, 2023

Automated Unsupervised Graph Representation Learning.

Zhenyu Hou, Yukuo Cen, Yuxiao Dong, Jie Zhang, Jie Tang

IEEE Trans. Knowl. Data Eng., March, 2023

TAP: Accelerating Large-Scale DNN Training Through Tensor Automatic Parallelisation.

Ziji Shi, Le Jiang, Ang Wang, Jie Zhang, Xianyan Jia, Yong Li, Chencan Wu, Jialin Li, Wei Lin

CoRR, 2023

2022

Whale: Efficient Giant Model Training over Heterogeneous GPUs.

Xianyan Jia, Le Jiang, Ang Wang, Wencong Xiao, Ziji Shi, Jie Zhang, Xinyuan Li, Langshi Chen, Yong Li, Zhen Zheng, Xiaoyong Liu, Wei Lin

Proceedings of the 2022 USENIX Annual Technical Conference, 2022

PICASSO: Unleashing the Potential of GPU-centric Training for Wide-and-deep Recommender Systems.

Yuanxing Zhang, Langshi Chen, Siran Yang, Man Yuan, Huimin Yi, Jie Zhang, Jiamang Wang, Jianbo Dong, Yunlong Xu, Yue Song, Yong Li, Di Zhang, Wei Lin, Lin Qu, Bo Zheng

Proceedings of the 38th IEEE International Conference on Data Engineering, 2022

2021

M6-10T: A Sharing-Delinking Paradigm for Efficient Multi-Trillion Parameter Pretraining.

Junyang Lin, An Yang, Jinze Bai, Chang Zhou, Le Jiang, Xianyan Jia, Ang Wang, Jie Zhang, Yong Li, Wei Lin, Jingren Zhou, Hongxia Yang

CoRR, 2021

Exploring Sparse Expert Models and Beyond.

An Yang, Junyang Lin, Rui Men, Chang Zhou, Le Jiang, Xianyan Jia, Ang Wang, Jie Zhang, Jiamang Wang, Yong Li, Di Zhang, Wei Lin, Lin Qu, Jingren Zhou, Hongxia Yang

CoRR, 2021

M6: A Chinese Multimodal Pretrainer.

Junyang Lin, Rui Men, An Yang, Chang Zhou, Ming Ding, Yichang Zhang, Peng Wang, Ang Wang, Le Jiang, Xianyan Jia, Jie Zhang, Jianwei Zhang, Xu Zou, Zhikang Li, Xiaodong Deng, Jie Liu, Jinbao Xue, Huiling Zhou, Jianxin Ma, Jin Yu, Yong Li, Wei Lin, Jingren Zhou, Jie Tang, Hongxia Yang

CoRR, 2021

2020

Whale: A Unified Distributed Training Framework.

Ang Wang, Xianyan Jia, Le Jiang, Jie Zhang, Yong Li, Wei Lin

CoRR, 2020

Graph Random Neural Network.

Wenzheng Feng, Jie Zhang, Yuxiao Dong, Yu Han, Huanbo Luan, Qian Xu, Qiang Yang, Jie Tang

CoRR, 2020

Graph Random Neural Networks for Semi-Supervised Learning on Graphs.

Wenzheng Feng, Jie Zhang, Yuxiao Dong, Yu Han, Huanbo Luan, Qian Xu, Qiang Yang, Evgeny Kharlamov, Jie Tang

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

2019

OAG: Toward Linking Large-scale Heterogeneous Entity Graphs.

Fanjin Zhang, Xiao Liu, Jie Tang, Yuxiao Dong, Peiran Yao, Jie Zhang, Xiaotao Gu, Yan Wang, Bin Shao, Rui Li, Kuansan Wang

Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2019

ProNE: Fast and Scalable Network Representation Learning.

Jie Zhang, Yuxiao Dong, Yan Wang, Jie Tang, Ming Ding

Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

A Fast Network Embedding Approach with Preserving Hierarchical Proximities.

Jie Zhang, Yan Wang, Jie Tang

Proceedings of the Fourth IEEE International Conference on Data Science in Cyberspace, 2019

2018

Spectral Network Embedding: A Fast and Scalable Method via Sparsity.

Jie Zhang, Yan Wang, Jie Tang, Ming Ding

CoRR, 2018

Semi-supervised Learning on Graphs with Generative Adversarial Nets.

Ming Ding, Jie Tang, Jie Zhang

Proceedings of the 27th ACM International Conference on Information and Knowledge Management, 2018

2016

Learning cascaded influence under partial monitoring.

Jie Zhang, Jiaqi Ma, Jie Tang

Proceedings of the 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, 2016