Stop the war!Остановите войну!
for scientists:
default search action
Google
Google Scholar
Semantic Scholar
Internet Archive Scholar
CiteSeerX
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://dblp.org/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
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
showing all ?? records
2020 – today
- 2024
[j20]Qitao Shi, Ya-Lin Zhang, Lu Yu, Feng Zhu, Longfei Li, Jun Zhou, Yanming Fang:
A distribution-free method for probabilistic prediction. Expert Syst. Appl. 237(Part B): 121396 (2024)- 2023
- [j19]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) - [j18]Caizhi Tang, Qing Cui, Longfei Li, Jun Zhou:
GINT: A Generative Interpretability method via perturbation in the latent space. Expert Syst. Appl. 232: 120570 (2023) - [j17]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) - [j16]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) - [j15]Jin Zhao, Yu Zhang, Ligang He, Qikun Li, Xiang Zhang, Xinyu Jiang, Hui Yu, Xiaofei Liao, Hai Jin, Lin Gu, Haikun Liu, Bingsheng He, Ji Zhang, Xianzheng Song, Lin Wang, Jun Zhou:
GraphTune: An Efficient Dependency-Aware Substrate to Alleviate Irregularity in Concurrent Graph Processing. ACM Trans. Archit. Code Optim. 20(3): 37:1-37:24 (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) - [c158]Yi-Xuan Sun, Ya-Lin Zhang, Wei Wang, Longfei Li, Jun Zhou:
Treatment Effect Estimation across Domains. CIKM 2023: 2352-2361 - [c157]Changxin Tian, Binbin Hu, Wayne Xin Zhao, Zhiqiang Zhang, Jun Zhou:
Periodicity May Be Emanative: Hierarchical Contrastive Learning for Sequential Recommendation. CIKM 2023: 2442-2451 - [c156]Ke Tu, Wei Qu, Zhengwei Wu, Zhiqiang Zhang, Zhongyi Liu, Yiming Zhao, Le Wu, Jun Zhou, Guannan Zhang:
Disentangled Interest importance aware Knowledge Graph Neural Network for Fund Recommendation. CIKM 2023: 2482-2491 - [c155]Lu Yu, Meng Li, Ya-Lin Zhang, Longfei Li, Jun Zhou:
FINRule: Feature Interactive Neural Rule Learning. CIKM 2023: 3020-3029 - [c154]Xu Min, Xiaolu Zhang, Bin Shen, Shuhan Wang, Yong He, Changsheng Li, Jun Zhou:
SeqGen: A Sequence Generator via User Side Information for Behavior Sparsity in Recommendation. CIKM 2023: 4205-4209 - [c153]Youshao Xiao, Shangchun Zhao, Zhenglei Zhou, Zhaoxin Huan, Lin Ju, Xiaolu Zhang, Lin Wang, Jun Zhou:
G-Meta: Distributed Meta Learning in GPU Clusters for Large-Scale Recommender Systems. CIKM 2023: 4365-4369 - [c152]Chilin Fu, Weichang Wu, Xiaolu Zhang, Jun Hu, Jing Wang, Jun Zhou:
Robust User Behavioral Sequence Representation via Multi-scale Stochastic Distribution Prediction. CIKM 2023: 4567-4573 - [c151]Hongyan Hao, Zhixuan Chu, Shiyi Zhu, Gangwei Jiang, Yan Wang, Caigao Jiang, James Y. Zhang, Wei Jiang, Siqiao Xue, Jun Zhou:
Continual Learning in Predictive Autoscaling. CIKM 2023: 4616-4622 - [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 - [i82]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) - [i81]Kaituo Feng, Changsheng Li, Xiaolu Zhang, Jun Zhou:
Towards Open Temporal Graph Neural Networks. CoRR abs/2303.15015 (2023) - [i80]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) - [i79]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) - [i78]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) - [i77]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) - [i76]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) - [i75]Chaochao Chen, Xiaohua Feng, Jun Zhou, Jianwei Yin, Xiaolin Zheng:
Federated Large Language Model: A Position Paper. CoRR abs/2307.08925 (2023) - [i74]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) - [i73]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) - [i72]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:
AntM2C: A Large Scale Dataset For Multi-Scenario Multi-Modal CTR Prediction. CoRR abs/2308.16437 (2023) - [i71]Yan Wang, Zhixuan Chu, Tao Zhou, Caigao Jiang, Hongyan Hao, Minjie Zhu, Xindong Cai, Qing Cui, Longfei Li, James Y. Zhang, Siqiao Xue, Jun Zhou:
Enhancing Asynchronous Time Series Forecasting with Contrastive Relational Inference. CoRR abs/2309.02868 (2023) - [i70]Qian Zhao, Zhengwei Wu, Zhiqiang Zhang, Jun Zhou:
Long-tail Augmented Graph Contrastive Learning for Recommendation. CoRR abs/2309.11177 (2023) - [i69]Chan Wu, Hanxiao Zhang, Lin Ju, Jinjing Huang, Youshao Xiao, Zhaoxin Huan, Siyuan Li, Fanzhuang Meng, Lei Liang, Xiaolu Zhang, Jun Zhou:
Rethinking Memory and Communication Cost for Efficient Large Language Model Training. CoRR abs/2310.06003 (2023) - [i68]Gangwei Jiang, Caigao Jiang, Siqiao Xue, James Y. Zhang, Jun Zhou, Defu Lian, Ying Wei:
Towards Anytime Fine-tuning: Continually Pre-trained Language Models with Hypernetwork Prompt. CoRR abs/2310.13024 (2023) - [i67]Zuoli Tang, Zhaoxin Huan, Zihao Li, Xiaolu Zhang, Jun Hu, Chilin Fu, Jun Zhou, Chenliang Li:
One Model for All: Large Language Models are Domain-Agnostic Recommendation Systems. CoRR abs/2310.14304 (2023) - [i66]Zhixuan Chu, Huaiyu Guo, Xinyuan Zhou, Yijia Wang, Fei Yu, Hong Chen, Wanqing Xu, Xin Lu, Qing Cui, Longfei Li, Jun Zhou, Sheng Li:
Data-Centric Financial Large Language Models. CoRR abs/2310.17784 (2023) - [i65]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. CoRR abs/2311.13864 (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]