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Jiezhong Qiu
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2020 – today
- 2024
- [j8]Zhongwei Wan
, Xin Liu
Spatio-temporal Contrastive Learning-enhanced GNNs for Session-based Recommendation. ACM Trans. Inf. Syst. 42(2): 58:1-58:26 (2024) - [c21]Bowen Wang, Chen Liang, Jiaze Wang, Jiezhong Qiu, Furui Liu, Shaogang Hao, Dong Li, Guangyong Chen, Xiaolong Zou, Pheng-Ann Heng:
DR-Label: Label Deconstruction and Reconstruction of GNN Models for Catalysis Systems. AAAI 2024: 15456-15465 - [c20]Fei Yang
Holmes: Towards Distributed Training Across Clusters with Heterogeneous NIC Environment. ICPP 2024: 514-523 - [i25]Kexin Chen, Hanqun Cao, Junyou Li, Yuyang Du, Menghao Guo, Xin Zeng, Lanqing Li, Jiezhong Qiu, Pheng-Ann Heng, Guangyong Chen:
An Autonomous Large Language Model Agent for Chemical Literature Data Mining. CoRR abs/2402.12993 (2024) - 2023
- [j7]Bo Chen, Ziwei Xie
Improved the heterodimer protein complex prediction with protein language models. Briefings Bioinform. 24(4) (2023) - [j6]Jiaxian Yan
Multi-task bioassay pre-training for protein-ligand binding affinity prediction. Briefings Bioinform. 25(1) (2023) - [j5]Shi-Xin Zhang
TensorCircuit: a Quantum Software Framework for the NISQ Era. Quantum 7: 912 (2023) - [j4]Yuyang Xie
Towards Lightweight and Automated Representation Learning System for Networks. IEEE Trans. Knowl. Data Eng. 35(9): 9613-9627 (2023) - [j3]Yuyang Xie
SketchNE: Embedding Billion-Scale Networks Accurately in One Hour. IEEE Trans. Knowl. Data Eng. 35(10): 10666-10680 (2023) - [c19]Shengyu Zhang, Yunze Tong, Kun Kuang, Fuli Feng, Jiezhong Qiu, Jin Yu, Zhou Zhao, Hongxia Yang, Zhongfei Zhang, Fei Wu:
Stable Prediction on Graphs with Agnostic Distribution Shifts. CDPD 2023: 49-74 - [i24]Jonathan P. Mailoa, Zhaofeng Ye, Jiezhong Qiu, Chang-Yu Hsieh, Shengyu Zhang:
Protein-Ligand Complex Generator & Drug Screening via Tiered Tensor Transform. CoRR abs/2301.00984 (2023) - [i23]Jonathan P. Mailoa, Xin Li, Jiezhong Qiu, Shengyu Zhang:
Multi-Constraint Molecular Generation using Sparsely Labelled Training Data for Localized High-Concentration Electrolyte Diluent Screening. CoRR abs/2301.04814 (2023) - [i22]Yuyang Xie, Jiezhong Qiu, Laxman Dhulipala, Wenjian Yu, Jie Tang, Richard Peng, Chi Wang:
Towards Lightweight and Automated Representation Learning System for Networks. CoRR abs/2302.07084 (2023) - [i21]Jiaxian Yan, Zhaofeng Ye, Ziyi Yang, Chengqiang Lu, Shengyu Zhang, Qi Liu, Jiezhong Qiu:
Multi-task Bioassay Pre-training for Protein-ligand Binding Affinity Prediction. CoRR abs/2306.04886 (2023) - [i20]Kexin Chen, Junyou Li, Kunyi Wang, Yuyang Du, Jiahui Yu, Jiamin Lu, Lanqing Li, Jiezhong Qiu, Qun Fang, Pheng-Ann Heng, Guangyong Chen:
Towards an Automatic AI Agent for Reaction Condition Recommendation in Chemical Synthesis. CoRR abs/2311.10776 (2023) - [i19]Fei Yang, Shuang Peng, Ning Sun
Holmes: Towards Distributed Training Across Clusters with Heterogeneous NIC Environment. CoRR abs/2312.03549 (2023) - 2022
- [c18]Zhengxiao Du, Yujie Qian, Xiao Liu, Ming Ding, Jiezhong Qiu, Zhilin Yang, Jie Tang:
GLM: General Language Model Pretraining with Autoregressive Blank Infilling. ACL (1) 2022: 320-335 - [c17]Yuyang Xie, Xu Feng, Xizhi Zhang, Jiezhong Qiu, Wenjian Yu:
Approximating Element-Wise Functions of Matrix with Improved Streaming Randomized SVD. ICTAI 2022: 122-130 - [c16]Xiao Liu, Shiyu Zhao, Kai Su, Yukuo Cen, Jiezhong Qiu, Mengdi Zhang, Wei Wu, Yuxiao Dong, Jie Tang:
Mask and Reason: Pre-Training Knowledge Graph Transformers for Complex Logical Queries. KDD 2022: 1120-1130 - [c15]Zixuan Ma
BaGuaLu: targeting brain scale pretrained models with over 37 million cores. PPoPP 2022: 192-204 - [i18]Xiao Liu, Shiyu Zhao, Kai Su, Yukuo Cen, Jiezhong Qiu, Mengdi Zhang, Wei Wu, Yuxiao Dong, Jie Tang:
Mask and Reason: Pre-Training Knowledge Graph Transformers for Complex Logical Queries. CoRR abs/2208.07638 (2022) - [i17]Zhongwei Wan, Benyou Wang, Xin Liu, Jiezhong Qiu, Boyu Li, Ting Guo, Guangyong Chen, Yang Wang:
Spatio-Temporal Contrastive Learning Enhanced GNNs for Session-based Recommendation. CoRR abs/2209.11461 (2022) - 2021
- [j2]Xu Han, Zhengyan Zhang, Ning Ding, Yuxian Gu, Xiao Liu
Pre-trained models: Past, present and future. AI Open 2: 225-250 (2021) - [c14]Junsheng Kong, Weizhao Li, Zeyi Liu, Ben Liao, Jiezhong Qiu, Chang-Yu Hsieh, Yi Cai, Shengyu Zhang:
Fast Extraction of Word Embedding from Q-contexts. CIKM 2021: 873-882 - [c13]Wei Jin, Yao Ma, Yiqi Wang, Xiaorui Liu, Jiliang Tang, Yukuo Cen, Jiezhong Qiu, Jie Tang, Chuan Shi, Yanfang Ye, Jiawei Zhang, Philip S. Yu:
Graph Representation Learning: Foundations, Methods, Applications and Systems. KDD 2021: 4044-4045 - [c12]Ming Ding, Yuxiao Dong, Xiao Liu, Jiezhong Qiu, Jie Tang, Zhilin Yang:
The International Workshop on Pretraining: Algorithms, Architectures, and Applications ([email protected] 2021). KDD 2021: 4119-4120 - [c11]Jiezhong Qiu, Laxman Dhulipala, Jie Tang, Richard Peng, Chi Wang:
LightNE: A Lightweight Graph Processing System for Network Embedding. SIGMOD Conference 2021: 2281-2289 - [i16]Zhengxiao Du, Yujie Qian, Xiao Liu, Ming Ding, Jiezhong Qiu, Zhilin Yang, Jie Tang:
All NLP Tasks Are Generation Tasks: A General Pretraining Framework. CoRR abs/2103.10360 (2021) - [i15]Jiaao He
FastMoE: A Fast Mixture-of-Expert Training System. CoRR abs/2103.13262 (2021) - [i14]Xu Han, Zhengyan Zhang, Ning Ding, Yuxian Gu, Xiao Liu, Yuqi Huo, Jiezhong Qiu, Liang Zhang, Wentao Han, Minlie Huang, Qin Jin, Yanyan Lan, Yang Liu, Zhiyuan Liu, Zhiwu Lu, Xipeng Qiu, Ruihua Song, Jie Tang, Ji-Rong Wen, Jinhui Yuan, Wayne Xin Zhao, Jun Zhu:
Pre-Trained Models: Past, Present and Future. CoRR abs/2106.07139 (2021) - [i13]Yijia Xiao
Modeling Protein Using Large-scale Pretrain Language Model. CoRR abs/2108.07435 (2021) - [i12]Junsheng Kong, Weizhao Li, Zeyi Liu, Ben Liao, Jiezhong Qiu, Chang-Yu Hsieh, Yi Cai, Shengyu Zhang:
Fast Extraction of Word Embedding from Q-contexts. CoRR abs/2109.07084 (2021) - [i11]Shengyu Zhang, Kun Kuang, Jiezhong Qiu, Jin Yu, Zhou Zhao, Hongxia Yang, Zhongfei Zhang, Fei Wu:
Stable Prediction on Graphs with Agnostic Distribution Shift. CoRR abs/2110.03865 (2021) - [i10]Yuyang Xie, Jiezhong Qiu, Wenjian Yu, Xu Feng, Yuxiang Chen, Jie Tang:
NetMF+: Network Embedding Based on Fast and Effective Single-Pass Randomized Matrix Factorization. CoRR abs/2110.12782 (2021) - [i9]Junsheng Kong, Weizhao Li, Ben Liao, Jiezhong Qiu, Chang-Yu Hsieh, Yi Cai, Jinhui Zhu, Shengyu Zhang:
Learning Large-scale Network Embedding from Representative Subgraph. CoRR abs/2112.01442 (2021) - 2020
- [c10]Jiezhong Qiu, Hao Ma, Omer Levy, Wen-tau Yih, Sinong Wang, Jie Tang:
Blockwise Self-Attention for Long Document Understanding. EMNLP (Findings) 2020: 2555-2565 - [c9]Jiezhong Qiu, Qibin Chen
GCC: Graph Contrastive Coding for Graph Neural Network Pre-Training. KDD 2020: 1150-1160 - [c8]Jiezhong Qiu, Chi Wang, Ben Liao, Richard Peng, Jie Tang:
A Matrix Chernoff Bound for Markov Chains and Its Application to Co-occurrence Matrices. NeurIPS 2020 - [i8]Jiezhong Qiu, Qibin Chen, Yuxiao Dong, Jing Zhang, Hongxia Yang, Ming Ding, Kuansan Wang, Jie Tang:
GCC: Graph Contrastive Coding for Graph Neural Network Pre-Training. CoRR abs/2006.09963 (2020) - [i7]Jiezhong Qiu, Chi Wang, Ben Liao, Richard Peng, Jie Tang:
Concentration Bounds for Co-occurrence Matrices of Markov Chains. CoRR abs/2008.02464 (2020)
2010 – 2019
- 2019
- [c7]Jiezhong Qiu, Yuxiao Dong, Hao Ma, Jian Li, Chi Wang, Kuansan Wang, Jie Tang:
NetSMF: Large-Scale Network Embedding as Sparse Matrix Factorization. WWW 2019: 1509-1520 - [i6]Guangyong Chen, Pengfei Chen, Chang-Yu Hsieh, Chee-Kong Lee, Benben Liao, Renjie Liao, Weiwen Liu, Jiezhong Qiu, Qiming Sun, Jie Tang, Richard S. Zemel, Shengyu Zhang:
Alchemy: A Quantum Chemistry Dataset for Benchmarking AI Models. CoRR abs/1906.09427 (2019) - [i5]Jiezhong Qiu, Yuxiao Dong, Hao Ma, Jian Li, Chi Wang, Kuansan Wang, Jie Tang:
NetSMF: Large-Scale Network Embedding as Sparse Matrix Factorization. CoRR abs/1906.11156 (2019) - [i4]Jiezhong Qiu, Hao Ma, Omer Levy, Scott Wen-tau Yih, Sinong Wang, Jie Tang:
Blockwise Self-Attention for Long Document Understanding. CoRR abs/1911.02972 (2019) - 2018
- [c6]Jiezhong Qiu, Jian Tang, Hao Ma, Yuxiao Dong, Kuansan Wang, Jie Tang:
DeepInf: Social Influence Prediction with Deep Learning. KDD 2018: 2110-2119 - [c5]Jiezhong Qiu, Yuxiao Dong, Hao Ma, Jian Li, Kuansan Wang, Jie Tang:
Network Embedding as Matrix Factorization: Unifying DeepWalk, LINE, PTE, and node2vec. WSDM 2018: 459-467 - [c4]Jiezhong Qiu:
Engagement and Incentives in Online Community: Observational Data, Prediction Models, and Field Experiments. WSDM 2018: 755-756 - [i3]Jiezhong Qiu, Jian Tang, Hao Ma, Yuxiao Dong, Kuansan Wang, Jie Tang:
DeepInf: Social Influence Prediction with Deep Learning. CoRR abs/1807.05560 (2018) - 2017
- [j1]Huijie Lin, Jia Jia, Jiezhong Qiu, Yongfeng Zhang, Guangyao Shen, Lexing Xie
Detecting Stress Based on Social Interactions in Social Networks. IEEE Trans. Knowl. Data Eng. 29(9): 1820-1833 (2017) - [i2]Jiezhong Qiu, Yuxiao Dong, Hao Ma, Jian Li, Kuansan Wang, Jie Tang:
Network Embedding as Matrix Factorization: Unifying DeepWalk, LINE, PTE, and node2vec. CoRR abs/1710.02971 (2017) - 2016
- [c3]Jiezhong Qiu, Jie Tang, Tracy Xiao Liu, Jie Gong
Modeling and Predicting Learning Behavior in MOOCs. WSDM 2016: 93-102 - [c2]Jiezhong Qiu, Yixuan Li, Jie Tang, Zheng Lu, Hao Ye, Bo Chen, Qiang Yang, John E. Hopcroft:
The Lifecycle and Cascade of WeChat Social Messaging Groups. WWW 2016: 311-320 - 2015
- [i1]Jiezhong Qiu, Yixuan Li, Jie Tang, Zheng Lu, Hao Ye, Bo Chen, Qiang Yang, John E. Hopcroft:
The Lifecycle and Cascade of Social Messaging Groups. CoRR abs/1512.07831 (2015) - 2014
- [c1]Jian Song, Yong Cui, Minming Li
Energy-traffic tradeoff cooperative offloading for mobile cloud computing. IWQoS 2014: 284-289
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last updated on 2024-10-07 21:26 CEST by the dblp team
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