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ORCIDJun Zhou 0011
Person information
- affiliation: Ant Financial Services Group, AI Department (Beijing), China
Other persons with the same name
- Jun Zhou — disambiguation page
- Jun Zhou 0001
![[0000-0001-5822-8233]](https://dblp1.uni-trier.de/img/orcid-mark.12x12.png "0000-0001-5822-8233")
— Griffith University, School of Information and Communication Technology, Nathan, QLD, Australia (and 1 more) - Jun Zhou 0002 — Broadcom Limited, Irvine, CA, USA (and 1 more)
- Jun Zhou 0003 — Donghua University, College of Information Sciences and Technology, Shanghai, China (and 1 more)
- Jun Zhou 0004 — Southwest University, School of Mathematics and Statistics, Chongqing, China
- Jun Zhou 0005 — Yangtze Normal University, School of Mathematics and Computer Science, Chongqing, China
- Jun Zhou 0006 — Chang'an University, School of Earth Sciences and Resources, Xi'an, China (and 1 more)
- Jun Zhou 0007 — Shanghai Jiao Tong University, Institute of Image Communication and Information Processing, China
- Jun Zhou 0008 — University of California, San Diego, USA
- Jun Zhou 0009 — University of Stuttgart, Germany
- Jun Zhou 0010 — Hohai University, College of Energy and Electrical Engineering, Nanjing, China (and 1 more)
- Jun Zhou 0012 — Zhongyuan Institute of Technology, College of Electronic Information, Zhengzhou, China
- Jun Zhou 0013 — University of Maryland, Earth System Science Interdisciplinary Center, College Park, MD, USA (and 1 more)
- Jun Zhou 0014 — National University of Singapore, School of Computing, Singapore
- Jun Zhou 0015 — Nanjing Agricultural University, College of Engineering, China
- Jun Zhou 0016 — Anhui University, School of Computer Science and Technology, Anhui Engineering Laboratory of IoT Security Technologies, Hefei, China
- Jun Zhou 0017 — University of Electronic Science and Technology of China, Smart ICs and Systems Research Group, Chengdu, China (and 2 more)
- Jun Zhou 0018 — East China Normal University, Shanghai Key Laboratory of Trustworthy Computing, China (and 1 more)
- Jun Zhou 0019 — Hunan Normal University, College of Mathematics and Statistics, Changsha, China (and 1 more)
- Jun Zhou 0020 — Northwestern Polytechnical University, Institute of Precision Guidance and Control / School of Astronautics, Xi'an, China
- Jun Zhou 0021 — Dalian University of Technology, School of Control Science and Engineering, China
- Jun Zhou 0022 — Chinese Academy of Sciences, Institute of Computing Technology, State Key Laboratory of Computer Architecture, Beijing, China
- Jun Zhou 0023 — Dalian Maritime University, Information Science and Technology College, China (and 1 more)
- Jun Zhou 0024 — Chinese Academy of Sciences, Key Laboratory of Speech Acoustics and Content Understanding, Institute of Acoustics, Beijing, China
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2020 – today
- 2023
[j17]Ya-Lin Zhang, Jun Zhou, Qitao Shi, Longfei Li:
Exploring the combination of self and mutual teaching for tabular-data-related semi-supervised regression. Expert Syst. Appl. 213(Part): 118931 (2023)- [j16]Ting Wu, Hong Qian, Ziqi Liu, Jun Zhou, Aimin Zhou:
Bi-objective evolutionary Bayesian network structure learning via skeleton constraint. Frontiers Comput. Sci. 17(6): 176350 (2023) - [j15]Jun Zhou, Ke Zhang, Lin Wang, Hua Wu, Yi Wang, Chaochao Chen:
SQLFlow: An Extensible Toolkit Integrating DB and AI. J. Mach. Learn. Res. 24: 116:1-116:9 (2023) - [j14]Yiming Wu, Zhiyuan Xie, Shouling Ji, Zhenguang Liu, Xuhong Zhang, Changting Lin, Shuiguang Deng, Jun Zhou, Ting Wang, Raheem Beyah:
Fraud-Agents Detection in Online Microfinance: A Large-Scale Empirical Study. IEEE Trans. Dependable Secur. Comput. 20(2): 1169-1185 (2023) - [j13]Pengyu Qiu, Xuhong Zhang, Shouling Ji, Tianyu Du, Yuwen Pu, Jun Zhou, Ting Wang:
Your Labels are Selling You Out: Relation Leaks in Vertical Federated Learning. IEEE Trans. Dependable Secur. Comput. 20(5): 3653-3668 (2023) - [j12]Kai Zhang, Qi Liu, Hao Qian, Biao Xiang, Qing Cui, Jun Zhou, Enhong Chen:
EATN: An Efficient Adaptive Transfer Network for Aspect-Level Sentiment Analysis. IEEE Trans. Knowl. Data Eng. 35(1): 377-389 (2023) - [j11]Feng Zhu, Yan Wang, Jun Zhou, Chaochao Chen, Longfei Li, Guanfeng Liu:
A Unified Framework for Cross-Domain and Cross-System Recommendations. IEEE Trans. Knowl. Data Eng. 35(2): 1171-1184 (2023) - [j10]Qinghua Zheng, Zhen Peng, Zhuohang Dang, Linchao Zhu, Ziqi Liu, Zhiqiang Zhang, Jun Zhou:
Deep Tabular Data Modeling With Dual-Route Structure-Adaptive Graph Networks. IEEE Trans. Knowl. Data Eng. 35(9): 9715-9727 (2023) - [c150]Jun Zhou, Qitao Shi, Yi Ding, Lin Wang, Longfei Li, Feng Zhu:
AntTune: An Efficient Distributed Hyperparameter Optimization System for Large-Scale Data. DASFAA (4) 2023: 477-489 - [c149]Ang Li, Jian Hu, Wei Lu, Ke Ding, Xiaolu Zhang, Jun Zhou, Yong He, Liang Zhang, Lihong Gu:
Global-Aware Model-Free Self-distillation for Recommendation System. DASFAA (4) 2023: 515-518 - [c148]Ke Tu, Zhengwei Wu, Binbin Hu, Zhiqiang Zhang, Peng Cui, Xiaolong Li, Jun Zhou:
A Scalable Social Recommendation Framework with Decoupled Graph Neural Network. DASFAA (4) 2023: 519-531 - [c147]Yangyang Hou, Daixin Wang, Binbin Hu, Ruoyu Zhuang, Zhiqiang Zhang, Jun Zhou, Feng Zhao, Yulin Kang, Zhanwen Qiao:
Unsupervised Fraud Transaction Detection on Dynamic Attributed Networks. DASFAA (4) 2023: 544-555 - [c146]Ya-Lin Zhang, Jun Zhou, Yankun Ren, Yue Zhang, Xinxing Yang, Meng Li, Qitao Shi, Longfei Li:
ALT: An Automatic System for Long Tail Scenario Modeling. ICDE 2023: 3017-3030 - [c145]Feng Zhu, Mingjie Zhong, Xinxing Yang, Longfei Li, Lu Yu, Tiehua Zhang, Jun Zhou, Chaochao Chen, Fei Wu, Guanfeng Liu, Yan Wang:
DCMT: A Direct Entire-Space Causal Multi-Task Framework for Post-Click Conversion Estimation. ICDE 2023: 3113-3125 - [c144]Weifan Wang, Binbin Hu, Zhicheng Peng, Mingjie Zhong, Zhiqiang Zhang, Zhongyi Liu, Guannan Zhang, Jun Zhou:
GARCIA: Powering Representations of Long-tail Query with Multi-granularity Contrastive Learning. ICDE 2023: 3182-3195 - [c143]Dalong Zhang, Xianzheng Song, Zhiyang Hu, Yang Li, Miao Tao, Binbin Hu, Lin Wang, Zhiqiang Zhang, Jun Zhou:
InferTurbo: A Scalable System for Boosting Full-graph Inference of Graph Neural Network over Huge Graphs. ICDE 2023: 3235-3247 - [c142]Meng Li, Jun Zhou, Lu Yu, Xiaoguang Huang, Yongfeng Gu, Yi Ding, Hao Ding, Longfei Li:
A Rule-based Decision System for Financial Applications. ICDE 2023: 3535-3548 - [c141]Kaituo Feng, Changsheng Li, Xiaolu Zhang, Jun Zhou:
Towards Open Temporal Graph Neural Networks. ICLR 2023 - [c140]Caizhi Tang, Huiyuan Wang, Xinyu Li, Qing Cui, Longfei Li, Jun Zhou:
Difference-in-Differences Meets Tree-based Methods: Heterogeneous Treatment Effects Estimation with Unmeasured Confounding. ICML 2023: 33792-33803 - [c139]Meikai Bao, Qi Liu, Kai Zhang, Ye Liu, Linan Yue, Longfei Li, Jun Zhou:
Keep Skills in Mind: Understanding and Implementing Skills in Commonsense Question Answering. IJCAI 2023: 5012-5020 - [c138]Daixin Wang, Zhiqiang Zhang, Yeyu Zhao, Kai Huang, Yulin Kang, Jun Zhou:
Financial Default Prediction via Motif-preserving Graph Neural Network with Curriculum Learning. KDD 2023: 2233-2242 - [c137]Zhaoxin Huan, Ang Li, Xiaolu Zhang, Xu Min, Jieyu Yang, Yong He, Jun Zhou:
SAMD: An Industrial Framework for Heterogeneous Multi-Scenario Recommendation. KDD 2023: 4175-4184 - [c136]Xiaoling Zang, Binbin Hu, Jun Chu, Zhiqiang Zhang, Guannan Zhang, Jun Zhou, Wenliang Zhong:
Commonsense Knowledge Graph towards Super APP and Its Applications in Alipay. KDD 2023: 5509-5519 - [c135]Jun Zhou, Yang Bao, Daohong Jian, Hua Wu:
PDAS: A Practical Distributed ADMM System for Large-Scale Linear Programming Problems at Alipay. KDD 2023: 5717-5727 - [c134]Shaowei Wei, Zhengwei Wu, Zhiqiang Zhang, Jun Zhou:
Boosting Adaptive Graph Augmented MLPs via Customized Knowledge Distillation. ECML/PKDD (3) 2023: 87-103 - [c133]Jun Hu, Xu Min, Xiaolu Zhang, Chilin Fu, Weichang Wu, Jun Zhou:
BCAD: An Interpretable Anomaly Transaction Detection System Based on Behavior Consistency. ECML/PKDD (6) 2023: 259-274 - [c132]Qian Zhao, Zhengwei Wu, Zhiqiang Zhang, Jun Zhou:
Long-Tail Augmented Graph Contrastive Learning for Recommendation. ECML/PKDD (4) 2023: 387-403 - [c131]Zuoli Tang, Lin Wang, Lixin Zou, Xiaolu Zhang, Jun Zhou, Chenliang Li:
Towards Multi-Interest Pre-training with Sparse Capsule Network. SIGIR 2023: 311-320 - [c130]Yonghui Yang, Zhengwei Wu, Le Wu, Kun Zhang, Richang Hong, Zhiqiang Zhang, Jun Zhou, Meng Wang:
Generative-Contrastive Graph Learning for Recommendation. SIGIR 2023: 1117-1126 - [c129]Jingyuan Li, Yue Zhang, Xuan Lin, Xinxing Yang, Ge Zhou, Longfei Li, Hong Chen, Jun Zhou:
TAML: Time-Aware Meta Learning for Cold-Start Problem in News Recommendation. SIGIR 2023: 2415-2419 - [c128]Ang Li, Jian Hu, Ke Ding, Xiaolu Zhang, Jun Zhou, Yong He, Xu Min:
Uncertainty-based Heterogeneous Privileged Knowledge Distillation for Recommendation System. SIGIR 2023: 2471-2475 - [c127]Chunjing Gan, Binbin Hu, Bo Huang, Tianyu Zhao, Yingru Lin, Wenliang Zhong, Zhiqiang Zhang, Jun Zhou, Chuan Shi:
Which Matters Most in Making Fund Investment Decisions? A Multi-granularity Graph Disentangled Learning Framework. SIGIR 2023: 2516-2520 - [c126]Sicong Xie, Binbin Hu, Fengze Li, Ziqi Liu, Zhiqiang Zhang, Wenliang Zhong, Jun Zhou:
COUPA: An Industrial Recommender System for Online to Offline Service Platforms. SIGIR 2023: 3235-3239 - [c125]Daohong Jian, Yang Bao, Jun Zhou, Hua Wu:
A Practical Online Allocation Framework at Industry-scale in Constrained Recommendation. SIGIR 2023: 3270-3274 - [c124]Han Zhao, Qing Cui, Xinyu Li, Rongzhou Bao, Longfei Li, Jun Zhou, Zhehao Liu, Jinghua Feng:
MDI: A Debiasing Method Combining Unbiased and Biased Data. SIGIR 2023: 3280-3284 - [c123]Junpeng Fang, Qing Cui, Gongduo Zhang, Caizhi Tang, Lihong Gu, Longfei Li, Jinjie Gu, Jun Zhou, Fei Wu:
Alleviating Matching Bias in Marketing Recommendations. SIGIR 2023: 3359-3363 - [c122]Yankun Ren, Xinxing Yang, Xingyu Lu, Longfei Li, Jun Zhou, Jinjie Gu, Guannan Zhang:
GreenSeq: Automatic Design of Green Networks for Sequential Recommendation Systems. SIGIR 2023: 3364-3368 - [c121]Ya-Lin Zhang, Yi-Xuan Sun, Fangfang Fan, Meng Li, Yeyu Zhao, Wei Wang, Longfei Li, Jun Zhou, Jinghua Feng:
A Framework for Detecting Frauds from Extremely Few Labels. WSDM 2023: 1124-1127 - [c120]Jun Zhou, Ke Zhang, Feng Zhu, Qitao Shi, Wenjing Fang, Lin Wang, Yi Wang:
ElasticDL: A Kubernetes-native Deep Learning Framework with Fault-tolerance and Elastic Scheduling. WSDM 2023: 1148-1151 - [c119]Yi Ding, Jun Zhou, Qing Cui, Lin Wang, Mengqi Zhang, Yang Dong:
DistriBayes: A Distributed Platform for Learning, Inference and Attribution on Large Scale Bayesian Network. WSDM 2023: 1184-1187 - [c118]Jianping Wei, Zhibo Zhu, Ziqi Liu, Zhiqiang Zhang, Jun Zhou:
AntTS: A Toolkit for Time Series Forecasting in Industrial Scenarios. WSDM 2023: 1192-1195 - [c117]Dingyuan Zhu, Daixin Wang, Zhiqiang Zhang, Kun Kuang, Yan Zhang, Yulin Kang, Jun Zhou:
Graph Neural Network with Two Uplift Estimators for Label-Scarcity Individual Uplift Modeling. WWW 2023: 395-405 - [c116]Jun Zhou, Meng Li, Lu Yu, Longfei Li, Fei Wu:
A Practical Rule Learning Framework for Risk Management. WWW (Companion Volume) 2023: 442-446 - [c115]Jun Zhou, Caizhi Tang, Qing Cui, Yi Ding, Longfei Li, Fei Wu:
DGBCT: A Scalable Distributed Gradient Boosting Causal Tree at Alipay. WWW (Companion Volume) 2023: 447-451 - [c114]Jun Zhou, Chilin Fu, Xiaolu Zhang:
Multi-Source Domain Adaptation via Latent Domain Reconstruction. WWW (Companion Volume) 2023: 523-527 - [c113]Lei Chen, Le Wu, Kun Zhang, Richang Hong, Defu Lian, Zhiqiang Zhang, Jun Zhou, Meng Wang:
Improving Recommendation Fairness via Data Augmentation. WWW 2023: 1012-1020 - [c112]Jianhao Jia, Hao Li, Kai Liu, Ziqi Liu, Jun Zhou, Nikolai Gravin, Zhihao Gavin Tang:
Online resource allocation in Markov Chains. WWW 2023: 3498-3507 - [i74]Feng Zhu, Mingjie Zhong, Xinxing Yang, Longfei Li, Lu Yu, Tiehua Zhang, Jun Zhou, Chaochao Chen, Fei Wu, Guanfeng Liu, Yan Wang:
DCMT: A Direct Entire-Space Causal Multi-Task Framework for Post-Click Conversion Estimation. CoRR abs/2302.06141 (2023) - [i73]Kaituo Feng, Changsheng Li, Xiaolu Zhang, Jun Zhou:
Towards Open Temporal Graph Neural Networks. CoRR abs/2303.15015 (2023) - [i72]Weifan Wang, Binbin Hu, Zhicheng Peng, Mingjie Zhong, Zhiqiang Zhang, Zhongyi Liu, Guannan Zhang, Jun Zhou:
GARCIA: Powering Representations of Long-tail Query with Multi-granularity Contrastive Learning. CoRR abs/2304.12537 (2023) - [i71]Sicong Xie, Binbin Hu, Fengze Li, Ziqi Liu, Zhiqiang Zhang, Wenliang Zhong, Jun Zhou:
COUPA: An Industrial Recommender System for Online to Offline Service Platforms. CoRR abs/2304.12549 (2023) - [i70]Ya-Lin Zhang, Jun Zhou, Yankun Ren, Yue Zhang, Xinxing Yang, Meng Li, Qitao Shi, Longfei Li:
ALT: An Automatic System for Long Tail Scenario Modeling. CoRR abs/2305.11390 (2023) - [i69]Dalong Zhang, Xianzheng Song, Zhiyang Hu, Yang Li, Miao Tao, Binbin Hu, Lin Wang, Zhiqiang Zhang, Jun Zhou:
InferTurbo: A Scalable System for Boosting Full-graph Inference of Graph Neural Network over Huge Graphs. CoRR abs/2307.00228 (2023) - [i68]Siqiao Xue, Xiaoming Shi, Zhixuan Chu, Yan Wang, Fan Zhou, Hongyan Hao, Caigao Jiang, Chen Pan, Yi Xu, James Y. Zhang, Qingsong Wen, Jun Zhou, Hongyuan Mei:
EasyTPP: Towards Open Benchmarking the Temporal Point Processes. CoRR abs/2307.08097 (2023) - [i67]Chaochao Chen, Xiaohua Feng, Jun Zhou, Jianwei Yin, Xiaolin Zheng:
Federated Large Language Model: A Position Paper. CoRR abs/2307.08925 (2023) - [i66]Hongyan Hao, Zhixuan Chu, Shiyi Zhu, Gangwei Jiang, Yan Wang, Caigao Jiang, James Zhang, Wei Jiang, Siqiao Xue, Jun Zhou:
Continual Learning in Predictive Autoscaling. CoRR abs/2307.15941 (2023) - [i65]Yan Wang, Zhixuan Chu, Xin Ouyang, Simeng Wang, Hongyan Hao, Yue Shen, Jinjie Gu, Siqiao Xue, James Y. Zhang, Qing Cui, Longfei Li, Jun Zhou, Sheng Li:
Enhancing Recommender Systems with Large Language Model Reasoning Graphs. CoRR abs/2308.10835 (2023) - 2022
- [j9]Jun-Peng Fang, Jun Zhou, Qing Cui, Caizhi Tang, Longfei Li:
Interpreting Model Predictions with Constrained Perturbation and Counterfactual Instances. Int. J. Pattern Recognit. Artif. Intell. 36(1): 2251001:1-2251001:23 (2022) - [j8]Jun Zhou, Chaochao Chen, Longfei Li, Zhiqiang Zhang, Xiaolin Zheng:
FinBrain 2.0: when finance meets trustworthy AI. Frontiers Inf. Technol. Electron. Eng. 23(12): 1747-1764 (2022) - [j7]Jun Zhou, Longfei Zheng, Chaochao Chen, Yan Wang, Xiaolin Zheng, Bingzhe Wu, Cen Chen, Li Wang, Jianwei Yin:
Toward Scalable and Privacy-preserving Deep Neural Network via Algorithmic-Cryptographic Co-design. ACM Trans. Intell. Syst. Technol. 13(4): 53:1-53:21 (2022) - [c111]Deyu Bo, Binbin Hu, Xiao Wang, Zhiqiang Zhang, Chuan Shi, Jun Zhou:
Regularizing Graph Neural Networks via Consistency-Diversity Graph Augmentations. AAAI 2022: 3913-3921 - [c110]Mengmei Zhang, Xiao Wang, Meiqi Zhu, Chuan Shi, Zhiqiang Zhang, Jun Zhou:
Robust Heterogeneous Graph Neural Networks against Adversarial Attacks. AAAI 2022: 4363-4370 - [c109]Lu Yu, Shichao Pei, Lizhong Ding, Jun Zhou, Longfei Li, Chuxu Zhang, Xiangliang Zhang:
SAIL: Self-Augmented Graph Contrastive Learning. AAAI 2022: 8927-8935 - [c108]Xinyu Li, Yilin Li, Qing Cui, Longfei Li, Jun Zhou:
Robust Direct Learning for Causal Data Fusion. ACML 2022: 611-626 - [c107]Yue Zhang, Xinxing Yang, Feng Zhu, Yalin Zhang, Meng Li, Qitao Shi, Longfei Li, Jun Zhou:
A Task-Aware Attention-Based Method for Improved Meta-Learning. APWeb/WAIM (2) 2022: 474-482 - [c106]Xinshun Feng, Herun Wan, Shangbin Feng, Hongrui Wang, Qinghua Zheng, Jun Zhou, Minnan Luo:
GraTO: Graph Neural Network Framework Tackling Over-smoothing with Neural Architecture Search. CIKM 2022: 520-529 - [c105]Lu Yu, Shichao Pei, Feng Zhu, Longfei Li, Jun Zhou, Chuxu Zhang, Xiangliang Zhang:
A Biased Sampling Method for Imbalanced Personalized Ranking. CIKM 2022: 2393-2402 - [c104]Meng Li, Lu Yu, Ya-Lin Zhang, Xiaoguang Huang, Qitao Shi, Qing Cui, Xinxing Yang, Longfei Li, Wei Zhu, Yanming Fang, Jun Zhou:
An Adaptive Framework for Confidence-constraint Rule Set Learning Algorithm in Large Dataset. CIKM 2022: 3252-3261 - [c103]Jun Zhou, Feng Qi, Zhigang Hua, Daohong Jian, Ziqi Liu, Hua Wu:
A Practical Distributed ADMM Solver for Billion-Scale Generalized Assignment Problems. CIKM 2022: 3715-3724 - [c102]Jun-Peng Fang, Caizhi Tang, Qing Cui, Feng Zhu, Longfei Li, Jun Zhou, Wei Zhu:
Semi-Supervised Learning with Data Augmentation for Tabular Data. CIKM 2022: 3928-3932 - [c101]Hao Qian, Qintong Wu, Minghao Li, Zhengwei Wu, Zhiqiang Zhang, Jun Zhou, Lihong Gu, Jinjie Gu:
FwSeqBlock: A Field-wise Approach for Modeling Behavior Representation in Sequential Recommendation. CIKM 2022: 4404-4408 - [c100]Jieyu Yang, Zhaoxin Huan, Yong He, Ke Ding, Liang Zhang, Xiaolu Zhang, Jun Zhou, Linjian Mo:
Task Similarity Aware Meta Learning for Cold-Start Recommendation. CIKM 2022: 4630-4634 - [c99]Lu Yu, Meng Li, Xiaoguang Huang, Wei Zhu, Yanming Fang, Jun Zhou, Longfei Li:
MetaRule: A Meta-path Guided Ensemble Rule Set Learning for Explainable Fraud Detection. CIKM 2022: 4650-4654 - [c98]Linge Jiang, Guiyang Wang, Zhibo Zhu, Binghao Wang, Runsheng Gan, Ziqi Liu, Jun Zhou:
A Real-time Post-processing System for Itinerary Recommendation. CIKM 2022: 4882-4886 - [c97]Yongfeng Gu, Yue Ning, Hao Ding, Kecai Gu, Daohong Jian, Zhou Xu, Hua Wu, Jun Zhou:
A Self-adaptive Indicator Selection Approach for Solving Credit Risk Assessment. COMPSAC 2022: 1567-1572 - [c96]Shih-Han Chan, Yinpeng Dong, Jun Zhu, Xiaolu Zhang, Jun Zhou:
BadDet: Backdoor Attacks on Object Detection. ECCV Workshops (1) 2022: 396-412 - [c95]Hao Ding, Yongfeng Gu, Hua Wu, Jun Zhou:
NL-SOMA-CLP for real parameter single objective bound constrained optimization. GECCO Companion 2022: 5-6 - [c94]Yongfeng Gu, Hao Ding, Hua Wu, Jun Zhou:
Opposite learning and multi-migrating strategy-based self-organizing migrating algorithm with the convergence monitoring mechanism. GECCO Companion 2022: 7-8 - [c93]Yue Ning, Daohong Jian, Hua Wu, Jun Zhou:
Zeroth-order covariance matrix adaptation evolution strategy for single objective bound constrained numerical optimization competition. GECCO Companion 2022: 9-10 - [c92]Yongfeng Gu, Hao Ding, Kecai Gu, Runsheng Gan, Xiaoguang Huang, Yanming Fang, Zhigang Hua, Hua Wu, Jifeng Xuan, Jun Zhou:
Heuristic strategies for solving the combinatorial optimization problem in real-world credit risk assessment. GECCO Companion 2022: 715-718 - [c91]Ang Li, Jian Hu, Chilin Fu, Xiaolu Zhang, Jun Zhou:
Attribute-Conditioned Face Swapping Network for Low-Resolution Images. ICASSP 2022: 2305-2309 - [c90]Weifan Wang, Xiaocheng Cheng, Ziqi Liu, Yu Lin, Yue Shen, Binbin Hu, Zhiqiang Zhang, Xiaodong Zeng, Jun Zhou, Jinjie Gu, Minnan Luo:
Intent Mining: A Social and Semantic Enhanced Topic Model for Operation-Friendly Digital Marketing. ICDE 2022: 3254-3267 - [c89]Borui Ye, Shuo Yang, Binbin Hu, Zhiqiang Zhang, Youqiang He, Kai Huang, Jun Zhou, Yanming Fang:
Gaia: Graph Neural Network with Temporal Shift aware Attention for Gross Merchandise Value Forecast in E-commerce. ICDE 2022: 3320-3326 - [c88]Chaochao Chen, Jun Zhou, Longfei Zheng, Huiwen Wu, Lingjuan Lyu, Jia Wu, Bingzhe Wu, Ziqi Liu, Li Wang, Xiaolin Zheng:
Vertically Federated Graph Neural Network for Privacy-Preserving Node Classification. IJCAI 2022: 1959-1965 - [c87]Binbin Hu, Zhengwei Wu, Jun Zhou, Ziqi Liu, Zhigang Huangfu, Zhiqiang Zhang, Chaochao Chen:
MERIT: Learning Multi-level Representations on Temporal Graphs. IJCAI 2022: 2073-2079 - [c86]Yunhao Zhang, Junchi Yan, Xiaolu Zhang, Jun Zhou, Xiaokang Yang:
Learning Mixture of Neural Temporal Point Processes for Multi-dimensional Event Sequence Clustering. IJCAI 2022: 3766-3772 - [c85]Daixin Wang, Zujian Weng, Zhengwei Wu, Zhiqiang Zhang, Peng Cui, Hongwei Zhao, Jun Zhou:
A Graph Learning Based Framework for Billion-Scale Offline User Identification. KDD 2022: 4001-4009 - [c84]Caizhi Tang, Huiyuan Wang, Xinyu Li, Qing Cui, Ya-Lin Zhang, Feng Zhu, Longfei Li, Jun Zhou, Linbo Jiang:
Debiased Causal Tree: Heterogeneous Treatment Effects Estimation with Unmeasured Confounding. NeurIPS 2022 - [c83]Yankun Ren, Longfei Li, Xinxing Yang, Jun Zhou:
AutoTransformer: Automatic Transformer Architecture Design for Time Series Classification. PAKDD (1) 2022: 143-155 - [c82]Xu Min, Xiaolu Zhang, Jun Zhou, Changxun Fan, Junlin Yu:
TAMOR: Tier-Aware Multi-objective Recommendation for Ant Fortune Financial Marketing. ECML/PKDD (6) 2022: 603-606 - [c81]Binbin Hu, Bin Shen, Ruize Wu, Zhiqiang Zhang, Yuetian Cao, Yong He, Liang Zhang, Linjian Mo, Jun Zhou:
Mixture of Graph Enhanced Expert Networks for Multi-task Recommendation. PRICAI (3) 2022: 3-16 - [c80]Yupeng Hou, Binbin Hu, Wayne Xin Zhao, Zhiqiang Zhang, Jun Zhou, Ji-Rong Wen:
Neural Graph Matching for Pre-training Graph Neural Networks. SDM 2022: 172-180 - [c79]Yanchao Tan, Carl Yang, Xiangyu Wei, Chaochao Chen, Weiming Liu, Longfei Li, Jun Zhou, Xiaolin Zheng:
MetaCare++: Meta-Learning with Hierarchical Subtyping for Cold-Start Diagnosis Prediction in Healthcare Data. SIGIR 2022: 449-459 - [c78]Zhaoxin Huan, Gongduo Zhang, Xiaolu Zhang, Jun Zhou, Qintong Wu, Lihong Gu, Jinjie Gu, Yong He, Yue Zhu, Linjian Mo:
An Industrial Framework for Cold-Start Recommendation in Zero-Shot Scenarios. SIGIR 2022: 3403-3407 - [c77]Yuhao Mao, Chong Fu, Saizhuo Wang, Shouling Ji, Xuhong Zhang, Zhenguang Liu, Jun Zhou, Alex X. Liu, Raheem Beyah, Ting Wang:
Transfer Attacks Revisited: A Large-Scale Empirical Study in Real Computer Vision Settings. SP 2022: 1423-1439 - [c76]Chong Fu, Xuhong Zhang, Shouling Ji, Jinyin Chen, Jingzheng Wu, Shanqing Guo, Jun Zhou, Alex X. Liu, Ting Wang:
Label Inference Attacks Against Vertical Federated Learning. USENIX Security Symposium 2022: 1397-1414 - [c75]Hao Qian, Qintong Wu, Kai Zhang, Zhiqiang Zhang, Lihong Gu, Xiaodong Zeng, Jun Zhou, Jinjie Gu:
Scope-aware Re-ranking with Gated Attention in Feed. WSDM 2022: 804-812 - [c74]Zhigang Huangfu, Gongduo Zhang, Zhengwei Wu, Qintong Wu, Zhiqiang Zhang, Lihong Gu, Jun Zhou, Jinjie Gu:
A Multi-Task Learning Approach for Delayed Feedback Modeling. WWW (Companion Volume) 2022: 116-120 - [c73]Hongrui Liu, Binbin Hu, Xiao Wang, Chuan Shi, Zhiqiang Zhang, Jun Zhou:
Confidence May Cheat: Self-Training on Graph Neural Networks under Distribution Shift. WWW 2022: 1248-1258 - [i64]Jihong Wang, Minnan Luo, Jundong Li, Ziqi Liu, Jun Zhou, Qinghua Zheng:
Robust Unsupervised Graph Representation Learning via Mutual Information Maximization. CoRR abs/2201.08557 (2022) - [i63]Hongrui Liu, Binbin Hu, Xiao Wang, Chuan Shi, Zhiqiang Zhang, Jun Zhou:
Confidence May Cheat: Self-Training on Graph Neural Networks under Distribution Shift. CoRR abs/2201.11349 (2022) - [i62]Yupeng Hou, Binbin Hu, Wayne Xin Zhao, Zhiqiang Zhang, Jun Zhou, Ji-Rong Wen:
Neural Graph Matching for Pre-training Graph Neural Networks. CoRR abs/2203.01597 (2022) - [i61]Qian Zhao, Shuo Yang, Binbin Hu, Zhiqiang Zhang, Yakun Wang, Yusong Chen, Jun Zhou, Chuan Shi:
An Effective Graph Learning based Approach for Temporal Link Prediction: The First Place of WSDM Cup 2022. CoRR abs/2203.01820 (2022) - [i60]Yuhao Mao, Chong Fu, Saizhuo Wang, Shouling Ji, Xuhong Zhang, Zhenguang Liu, Jun Zhou, Alex X. Liu, Raheem Beyah, Ting Wang:
Transfer Attacks Revisited: A Large-Scale Empirical Study in Real Computer Vision Settings. CoRR abs/2204.04063 (2022) - [i59]Binbin Hu, Zhiyang Hu, Zhiqiang Zhang, Jun Zhou, Chuan Shi:
KGNN: Distributed Framework for Graph Neural Knowledge Representation. CoRR abs/2205.08285 (2022) - [i58]