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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://dblp.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
- 2024
[j27]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)- [j26]Jun Zhou, Hongbin Chen:
Finite Element Method on locally refined composite meshes for Dirichlet fractional Laplacian. J. Comput. Sci. 82: 102433 (2024) - [j25]Chao-Chao Chen, Fei Zheng, Jamie Cui, Yuwei Cao, Guanfeng Liu, Jia Wu, Jun Zhou:
Survey and open problems in privacy-preserving knowledge graph: merging, query, representation, completion, and applications. Int. J. Mach. Learn. Cybern. 15(8): 3513-3532 (2024) - [j24]Chaochao Chen, Xiaohua Feng, Yuyuan Li, Lingjuan Lyu, Jun Zhou, Xiaolin Zheng, Jianwei Yin:
Integration of large language models and federated learning. Patterns 5(12): 101098 (2024) - [j23]Chenghui Shi, Shouling Ji, Xudong Pan, Xuhong Zhang, Mi Zhang, Min Yang, Jun Zhou, Jianwei Yin, Ting Wang:
Towards Practical Backdoor Attacks on Federated Learning Systems. IEEE Trans. Dependable Secur. Comput. 21(6): 5431-5447 (2024) - [j22]Weichang Wu, Xiaolu Zhang, Shiwan Zhao, Chilin Fu, Jun Zhou:
Multi-Task Decouple Learning With Hierarchical Attentive Point Process. IEEE Trans. Knowl. Data Eng. 36(4): 1741-1757 (2024) - [j21]Yonghui Yang, Le Wu, Kun Zhang, Richang Hong, Hailin Zhou, Zhiqiang Zhang, Jun Zhou, Meng Wang:
Hyperbolic Graph Learning for Social Recommendation. IEEE Trans. Knowl. Data Eng. 36(12): 8488-8501 (2024) - [j20]Kun Zhang, Le Wu, Guangyi Lv, Enhong Chen, Shulan Ruan, Jing Liu, Zhiqiang Zhang, Jun Zhou, Meng Wang:
Description-Enhanced Label Embedding Contrastive Learning for Text Classification. IEEE Trans. Neural Networks Learn. Syst. 35(10): 14889-14902 (2024) - [c211]Fan Zhou, Chen Pan, Lintao Ma, Yu Liu, Siqiao Xue, James Y. Zhang, Jun Zhou, Hongyuan Mei, Weitao Lin, Zi Zhuang, Wenxin Ning, Yunhua Hu:
GMP-AR: Granularity Message Passing and Adaptive Reconciliation for Temporal Hierarchy Forecasting. AAAI 2024: 9414-9421 - [c210]Junpeng Fang, Gongduo Zhang, Qing Cui, Caizhi Tang, Lihong Gu, Longfei Li, Jinjie Gu, Jun Zhou:
Backdoor Adjustment via Group Adaptation for Debiased Coupon Recommendations. AAAI 2024: 11944-11952 - [c209]Hao Qian, Hongting Zhou, Qian Zhao, Hao Chen, Hongxiang Yao, Jingwei Wang, Ziqi Liu, Fei Yu, Zhiqiang Zhang, Jun Zhou:
MDGNN: Multi-Relational Dynamic Graph Neural Network for Comprehensive and Dynamic Stock Investment Prediction. AAAI 2024: 14642-14650 - [c208]Yan Wang, Zhixuan Chu, Xin Ouyang, Simeng Wang, Hongyan Hao, Yue Shen, Jinjie Gu, Siqiao Xue, James Zhang, Qing Cui, Longfei Li, Jun Zhou, Sheng Li:
LLMRG: Improving Recommendations through Large Language Model Reasoning Graphs. AAAI 2024: 19189-19196 - [c207]Yin Gu, Kai Zhang, Qi Liu, Weibo Gao, Longfei Li, Jun Zhou:
π-Light: Programmatic Interpretable Reinforcement Learning for Resource-Limited Traffic Signal Control. AAAI 2024: 21107-21115 - [c206]Xiao Tan, Zhaoyang Wang, Hao Qian, Jun Zhou, Peibo Duan, Dian Shen, Meng Wang, Beilun Wang:
Factor Model-Based Large Covariance Estimation from Streaming Data Using a Knowledge-Based Sketch Matrix. CIKM 2024: 2210-2219 - [c205]Zuoli Tang, Zhaoxin Huan, Zihao Li, Shirui Hu, Xiaolu Zhang, Jun Zhou, Lixin Zou, Chenliang Li:
TEXT CAN BE FAIR: Mitigating Popularity Bias with PLMs by Learning Relative Preference. CIKM 2024: 2240-2249 - [c204]Fuwei Zhang, Zhao Zhang, Fuzhen Zhuang, Zhiqiang Zhang, Jun Zhou, Deqing Wang:
Multi-view Temporal Knowledge Graph Reasoning. CIKM 2024: 4263-4267 - [c203]Shiyu Wang, Zhixuan Chu, Yinbo Sun, Yu Liu, Yuliang Guo, Yang Chen, Huiyang Jian, Lintao Ma, Xingyu Lu, Jun Zhou:
Multiscale Representation Enhanced Temporal Flow Fusion Model for Long-Term Workload Forecasting. CIKM 2024: 4948-4956 - [c202]Dong-Dong Wu, Chilin Fu, Weichang Wu, Wenwen Xia, Xiaolu Zhang, Jun Zhou, Min-Ling Zhang:
Efficient Model Stealing Defense with Noise Transition Matrix. CVPR 2024: 24305-24315 - [c201]Kehang Wang, Ye Liu, Kai Zhang, Qi Liu, Yankun Ren, Xinxing Yang, Longfei Li, Jun Zhou:
QoMRC: Query-oriented Machine Reading Comprehension Framework for Aspect Sentiment Triplet Extraction. DASFAA (5) 2024: 173-189 - [c200]Mingyue Cheng, Hao Zhang, Qi Liu, Fajie Yuan, Zhi Li, Zhenya Huang, Enhong Chen, Jun Zhou, Longfei Li:
Empowering Sequential Recommendation from Collaborative Signals and Semantic Relatedness. DASFAA (3) 2024: 196-211 - [c199]Yue Zhang, Xinxing Yang, Feng Zhu, Longfei Li, Linbo Jiang, Jun Zhou:
Distributed Meta-learning for Large-Scale Multi-institution Credit Default Risk Prediction. DASFAA (7) 2024: 313-326 - [c198]Borui Ye, Shuo Yang, Meiqi Zhu, Binbin Hu, Daixin Wang, Zhiqiang Zhang, Youqiang He, Zhiyang Hu, Huimei He, Jun Zhou:
Granola: Graph Neural Network Tackling Tabular Data for Online Loan Default Prediction. DASFAA (7) 2024: 436-440 - [c197]Yuemin Chen, Feifan Wu, Jingwei Wang, Hao Qian, Ziqi Liu, Zhiqiang Zhang, Jun Zhou, Meng Wang:
Knowledge-augmented Financial Market Analysis and Report Generation. EMNLP (Industry Track) 2024: 1207-1217 - [c196]Jintian Zhang, Cheng Peng, Mengshu Sun, Xiang Chen, Lei Liang, Zhiqiang Zhang, Jun Zhou, Huajun Chen, Ningyu Zhang:
OneGen: Efficient One-Pass Unified Generation and Retrieval for LLMs. EMNLP (Findings) 2024: 4088-4119 - [c195]Junjie Wang, Mingyang Chen, Binbin Hu, Dan Yang, Ziqi Liu, Yue Shen, Peng Wei, Zhiqiang Zhang, Jinjie Gu, Jun Zhou, Jeff Z. Pan, Wen Zhang, Huajun Chen:
Learning to Plan for Retrieval-Augmented Large Language Models from Knowledge Graphs. EMNLP (Findings) 2024: 7813-7835 - [c194]Jiahui Li, Hanlin Zhang, Fengda Zhang, Tai-Wei Chang, Kun Kuang, Long Chen, Jun Zhou:
Optimizing Language Models with Fair and Stable Reward Composition in Reinforcement Learning. EMNLP 2024: 10122-10140 - [c193]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 Event Sequence Modeling with Contrastive Relational Inference. ICASSP 2024: 6145-6149 - [c192]Shiyu Wang, Haixu Wu, Xiaoming Shi, Tengge Hu, Huakun Luo, Lintao Ma, James Y. Zhang, Jun Zhou:
TimeMixer: Decomposable Multiscale Mixing for Time Series Forecasting. ICLR 2024 - [c191]Siqiao Xue, Xiaoming Shi, Zhixuan Chu, Yan Wang, Hongyan Hao, Fan Zhou, Caigao Jiang, Chen Pan, James Y. Zhang, Qingsong Wen, Jun Zhou, Hongyuan Mei:
EasyTPP: Towards Open Benchmarking Temporal Point Processes. ICLR 2024 - [c190]Kaituo Feng, Changsheng Li, Xiaolu Zhang, Jun Zhou, Ye Yuan, Guoren Wang:
Keypoint-based Progressive Chain-of-Thought Distillation for LLMs. ICML 2024 - [c189]Yi-Xuan Sun, Ya-Lin Zhang, Bin Han, Longfei Li, Jun Zhou:
Self-cognitive Denoising in the Presence of Multiple Noisy Label Sources. ICML 2024 - [c188]Kaiwen Xue, Yuhao Zhou, Shen Nie, Xu Min, Xiaolu Zhang, Jun Zhou, Chongxuan Li:
Unifying Bayesian Flow Networks and Diffusion Models through Stochastic Differential Equations. ICML 2024 - [c187]Xiuyuan Qi, Ye Liu, Shuang Hao, Zherong Liu, Kun Huang, Minghui Yang, Liang Zhou, Jun Zhou:
A High-Performance ORB Accelerator with Algorithm and Hardware Co-design for Visual Localization. ISCAS 2024: 1-5 - [c186]Yupeng Wu, Zhibo Zhu, Chaoyi Ma, Hong Qian, Xingyu Lu, Yangwenhui Zhang, Xiaobo Qin, Binjie Fei, Jun Zhou, Aimin Zhou:
Cost-Efficient Fraud Risk Optimization with Submodularity in Insurance Claim. KDD 2024: 3448-3459 - [c185]Yongfeng Gu, Yupeng Wu, Huakang Lu, Xingyu Lu, Hong Qian, Jun Zhou, Aimin Zhou:
LASCA: A Large-Scale Stable Customer Segmentation Approach to Credit Risk Assessment. KDD 2024: 5006-5017 - [c184]Feng Zhu, Xinxing Yang, Longfei Li, Jun Zhou:
An Active Masked Attention Framework for Many-to-Many Cross-Domain Recommendations. ACM Multimedia 2024: 9680-9689 - [c183]Bin Han, Yi-Xuan Sun, Ya-Lin Zhang, Libang Zhang, Haoran Hu, Longfei Li, Jun Zhou, Guo Ye, Huimei He:
Collaborative Refining for Learning from Inaccurate Labels. NeurIPS 2024 - [c182]Bin Han, Ya-Lin Zhang, Lu Yu, Biying Chen, Longfei Li, Jun Zhou:
Modeling Treatment Effect with Cross-Domain Data. PAKDD (1) 2024: 365-377 - [c181]Yuxin Guo, Cheng Yang, Chuan Shi, Ke Tu, Zhengwei Wu, Zhiqiang Zhang, Jun Zhou:
Adaptively Denoising Graph Neural Networks for Knowledge Distillation. ECML/PKDD (8) 2024: 253-269 - [c180]Changxin Tian, Binbin Hu, Chunjing Gan, Haoyu Chen, Zhuo Zhang, Li Yu, Ziqi Liu, Zhiqiang Zhang, Jun Zhou, Jiawei Chen:
ReLand: Integrating Large Language Models' Insights into Industrial Recommenders via a Controllable Reasoning Pool. RecSys 2024: 63-73 - [c179]Yankun Ren, Zhongde Chen, Xinxing Yang, Longfei Li, Cong Jiang, Lei Cheng, Bo Zhang, Linjian Mo, Jun Zhou:
Enhancing Sequential Recommenders with Augmented Knowledge from Aligned Large Language Models. SIGIR 2024: 345-354 - [c178]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, Chenliang Li, Fajie Yuan:
Exploring Multi-Scenario Multi-Modal CTR Prediction with a Large Scale Dataset. SIGIR 2024: 1232-1241 - [c177]Binzong Geng, Zhaoxin Huan, Xiaolu Zhang, Yong He, Liang Zhang, Fajie Yuan, Jun Zhou, Linjian Mo:
Breaking the Length Barrier: LLM-Enhanced CTR Prediction in Long Textual User Behaviors. SIGIR 2024: 2311-2315 - [c176]Cong Jiang, Zhongde Chen, Bo Zhang, Yankun Ren, Xin Dong, Lei Cheng, Xinxing Yang, Longfei Li, Jun Zhou, Linjian Mo:
GATS: Generative Audience Targeting System for Online Advertising. SIGIR 2024: 2920-2924 - [c175]Ningyu Zhang, Zekun Xi, Yujie Luo, Peng Wang, Bozhong Tian, Yunzhi Yao, Jintian Zhang, Shumin Deng, Mengshu Sun, Lei Liang, Zhiqiang Zhang, Xiaowei Zhu, Jun Zhou, Huajun Chen:
OneEdit: A Neural-Symbolic Collaboratively Knowledge Editing System. VLDB Workshops 2024 - [c174]Chunjing Gan, Bo Huang, Binbin Hu, Jian Ma, Zhiqiang Zhang, Jun Zhou, Guannan Zhang, Wenliang Zhong:
PEACE: Prototype lEarning Augmented transferable framework for Cross-domain rEcommendation. WSDM 2024: 228-237 - [c173]Yakun Wang, Binbin Hu, Shuo Yang, Meiqi Zhu, Zhiqiang Zhang, Qiyang Zhang, Jun Zhou, Guo Ye, Huimei He:
Not All Negatives Are Worth Attending to: Meta-Bootstrapping Negative Sampling Framework for Link Prediction. WSDM 2024: 760-768 - [c172]Ya-Lin Zhang, Caizhi Tang, Lu Yu, Jun Zhou, Longfei Li, Qing Cui, Fangfang Fan, Linbo Jiang, Xiaosong Zhao:
Domain Level Interpretability: Interpreting Black-box Model with Domain-specific Embedding. WSDM 2024: 1102-1105 - [c171]Junpeng Fang, Gongduo Zhang, Qing Cui, Lihong Gu, Longfei Li, Jinjie Gu, Jun Zhou:
Counterfactual Data Augmentation for Debiased Coupon Recommendations Based on Potential Knowledge. WWW (Companion Volume) 2024: 93-102 - [c170]Jun Hu, Wenwen Xia, Xiaolu Zhang, Chilin Fu, Weichang Wu, Zhaoxin Huan, Ang Li, Zuoli Tang, Jun Zhou:
Enhancing Sequential Recommendation via LLM-based Semantic Embedding Learning. WWW (Companion Volume) 2024: 103-111 - [c169]Shuhan Wang, Bin Shen, Xu Min, Yong He, Xiaolu Zhang, Liang Zhang, Jun Zhou, Linjian Mo:
Aligned Side Information Fusion Method for Sequential Recommendation. WWW (Companion Volume) 2024: 112-120 - [c168]Cheng Yang, Chengdong Yang, Chuan Shi, Yawen Li, Zhiqiang Zhang, Jun Zhou:
Calibrating Graph Neural Networks from a Data-centric Perspective. WWW 2024: 745-755 - [c167]Yongduo Sui, Caizhi Tang, Zhixuan Chu, Junfeng Fang, Yuan Gao, Qing Cui, Longfei Li, Jun Zhou, Xiang Wang:
Invariant Graph Learning for Causal Effect Estimation. WWW 2024: 2552-2562 - [c166]Shaowei Wei, Zhengwei Wu, Xin Li, Qintong Wu, Zhiqiang Zhang, Jun Zhou, Lihong Gu, Jinjie Gu:
Leave No One Behind: Online Self-Supervised Self-Distillation for Sequential Recommendation. WWW 2024: 3767-3776 - [c165]Yuling Wang, Changxin Tian, Binbin Hu, Yanhua Yu, Ziqi Liu, Zhiqiang Zhang, Jun Zhou, Liang Pang, Xiao Wang:
Can Small Language Models be Good Reasoners for Sequential Recommendation? WWW 2024: 3876-3887 - [i121]Ningyu Zhang, Yunzhi Yao, Bozhong Tian, Peng Wang, Shumin Deng, Mengru Wang, Zekun Xi, Shengyu Mao, Jintian Zhang, Yuansheng Ni, Siyuan Cheng, Ziwen Xu, Xin Xu, Jia-Chen Gu, Yong Jiang, Pengjun Xie, Fei Huang, Lei Liang, Zhiqiang Zhang, Xiaowei Zhu, Jun Zhou, Huajun Chen:
A Comprehensive Study of Knowledge Editing for Large Language Models. CoRR abs/2401.01286 (2024) - [i120]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. CoRR abs/2401.04338 (2024) - [i119]Hao Qian, Hongting Zhou, Qian Zhao, Hao Chen, Hongxiang Yao, Jingwei Wang, Ziqi Liu, Fei Yu, Zhiqiang Zhang, Jun Zhou:
MDGNN: Multi-Relational Dynamic Graph Neural Network for Comprehensive and Dynamic Stock Investment Prediction. CoRR abs/2402.06633 (2024) - [i118]Yuling Wang, Changxin Tian, Binbin Hu, Yanhua Yu, Ziqi Liu, Zhiqiang Zhang, Jun Zhou, Liang Pang, Xiao Wang:
Can Small Language Models be Good Reasoners for Sequential Recommendation? CoRR abs/2403.04260 (2024) - [i117]Mingyue Cheng, Hao Zhang, Qi Liu, Fajie Yuan, Zhi Li, Zhenya Huang, Enhong Chen, Jun Zhou, Longfei Li:
Empowering Sequential Recommendation from Collaborative Signals and Semantic Relatedness. CoRR abs/2403.07623 (2024) - [i116]Binzong Geng, Zhaoxin Huan, Xiaolu Zhang, Yong He, Liang Zhang, Fajie Yuan, Jun Zhou, Linjian Mo:
Breaking the Length Barrier: LLM-Enhanced CTR Prediction in Long Textual User Behaviors. CoRR abs/2403.19347 (2024) - [i115]Shaowei Wei, Zhengwei Wu, Xin Li, Qintong Wu, Zhiqiang Zhang, Jun Zhou, Lihong Gu, Jinjie Gu:
Leave No One Behind: Online Self-Supervised Self-Distillation for Sequential Recommendation. CoRR abs/2404.07219 (2024) - [i114]Youshao Xiao, Lin Ju, Zhenglei Zhou, Siyuan Li, Zhaoxin Huan, Dalong Zhang, Rujie Jiang, Lin Wang, Xiaolu Zhang, Lei Liang, Jun Zhou:
AntDT: A Self-Adaptive Distributed Training Framework for Leader and Straggler Nodes. CoRR abs/2404.09679 (2024) - [i113]Kaiwen Xue, Yuhao Zhou, Shen Nie, Xu Min, Xiaolu Zhang, Jun Zhou, Chongxuan Li:
Unifying Bayesian Flow Networks and Diffusion Models through Stochastic Differential Equations. CoRR abs/2404.15766 (2024) - [i112]Shiyu Wang, Haixu Wu, Xiaoming Shi, Tengge Hu, Huakun Luo, Lintao Ma, James Y. Zhang, Jun Zhou:
TimeMixer: Decomposable Multiscale Mixing for Time Series Forecasting. CoRR abs/2405.14616 (2024) - [i111]Fan Liu, Liang Yao, Chuanyi Zhang, Ting Wu, Xinlei Zhang, Xiruo Jiang, Jun Zhou:
Scale-Invariant Feature Disentanglement via Adversarial Learning for UAV-based Object Detection. CoRR abs/2405.15465 (2024) - [i110]Kaituo Feng, Changsheng Li, Xiaolu Zhang, Jun Zhou, Ye Yuan, Guoren Wang:
Keypoint-based Progressive Chain-of-Thought Distillation for LLMs. CoRR abs/2405.16064 (2024) - [i109]Chunjing Gan, Binbin Hu, Bo Huang, Ziqi Liu, Jian Ma, Zhiqiang Zhang, Wenliang Zhong, Jun Zhou:
Your decision path does matter in pre-training industrial recommenders with multi-source behaviors. CoRR abs/2405.17132 (2024) - [i108]Chunjing Gan, Dan Yang, Binbin Hu, Hanxiao Zhang, Siyuan Li, Ziqi Liu, Yue Shen, Lin Ju, Zhiqiang Zhang, Jinjie Gu, Lei Liang, Jun Zhou:
Similarity is Not All You Need: Endowing Retrieval Augmented Generation with Multi Layered Thoughts. CoRR abs/2405.19893 (2024) - [i107]Boxin Zhao, Weishi Wang, Dingyuan Zhu, Ziqi Liu, Dong Wang, Zhiqiang Zhang, Jun Zhou, Mladen Kolar:
Personalized Binomial DAGs Learning with Network Structured Covariates. CoRR abs/2406.06829 (2024) - [i106]Gangwei Jiang, Caigao Jiang, Zhaoyi Li, Siqiao Xue, Jun Zhou, Linqi Song, Defu Lian, Ying Wei:
Interpretable Catastrophic Forgetting of Large Language Model Fine-tuning via Instruction Vector. CoRR abs/2406.12227 (2024) - [i105]Fan Zhou, Chen Pan, Lintao Ma, Yu Liu, James Y. Zhang, Jun Zhou, Hongyuan Mei, Weitao Lin, Zi Zhuang, Wenxin Ning, Yunhua Hu, Siqiao Xue:
GMP-AR: Granularity Message Passing and Adaptive Reconciliation for Temporal Hierarchy Forecasting. CoRR abs/2406.12242 (2024) - [i104]Junjie Wang, Mingyang Chen, Binbin Hu, Dan Yang, Ziqi Liu, Yue Shen, Peng Wei, Zhiqiang Zhang, Jinjie Gu, Jun Zhou, Jeff Z. Pan, Wen Zhang, Huajun Chen:
Learning to Plan for Retrieval-Augmented Large Language Models from Knowledge Graphs. CoRR abs/2406.14282 (2024) - [i103]Shiyu Wang, Zhixuan Chu, Yinbo Sun, Yu Liu, Yuliang Guo, Yang Chen, Huiyang Jian, Lintao Ma, Xingyu Lu, Jun Zhou:
Multiscale Representation Enhanced Temporal Flow Fusion Model for Long-Term Workload Forecasting. CoRR abs/2407.19697 (2024) - [i102]Fan Liu, Wenwen Cai, Jian Huo, Chuanyi Zhang, Delong Chen, Jun Zhou:
Making Large Vision Language Models to be Good Few-shot Learners. CoRR abs/2408.11297 (2024) - [i101]Jintian Zhang, Cheng Peng, Mengshu Sun, Xiang Chen, Lei Liang, Zhiqiang Zhang, Jun Zhou, Huajun Chen, Ningyu Zhang:
OneGen: Efficient One-Pass Unified Generation and Retrieval for LLMs. CoRR abs/2409.05152 (2024) - [i100]Ningyu Zhang, Zekun Xi, Yujie Luo, Peng Wang, Bozhong Tian, Yunzhi Yao, Jintian Zhang, Shumin Deng, Mengshu Sun, Lei Liang, Zhiqiang Zhang, Xiaowei Zhu, Jun Zhou, Huajun Chen:
OneEdit: A Neural-Symbolic Collaboratively Knowledge Editing System. CoRR abs/2409.07497 (2024) - [i99]Shiyu Miao, Delong Chen, Fan Liu, Chuanyi Zhang, Yanhui Gu, Shengjie Guo, Jun Zhou:
Prompting DirectSAM for Semantic Contour Extraction in Remote Sensing Images. CoRR abs/2410.06194 (2024) - [i98]Caigao Jiang, Xiang Shu, Hong Qian, Xingyu Lu, Jun Zhou, Aimin Zhou, Yang Yu:
LLMOPT: Learning to Define and Solve General Optimization Problems from Scratch. CoRR abs/2410.13213 (2024) - [i97]Binbin Hu, Zhicheng An, Zhengwei Wu, Ke Tu, Ziqi Liu, Zhiqiang Zhang, Jun Zhou, Yufei Feng, Jiawei Chen:
Graph Disentangle Causal Model: Enhancing Causal Inference in Networked Observational Data. CoRR abs/2412.03913 (2024) - [i96]Guangwenjie Zou, Liang Yao, Fan Liu, Chuanyi Zhang, Xin Li, Ning Chen, Shengxiang Xu, Jun Zhou:
RemoteTrimmer: Adaptive Structural Pruning for Remote Sensing Image Classification. CoRR abs/2412.12603 (2024) - [i95]Jiahui Li, Tai-Wei Chang, Kun Kuang, Ximing Li, Long Chen, Jun Zhou:
Learning Causal Transition Matrix for Instance-dependent Label Noise. CoRR abs/2412.13516 (2024) - [i94]Yujie Luo, Xiangyuan Ru, Kangwei Liu, Lin Yuan, Mengshu Sun, Ningyu Zhang, Lei Liang, Zhiqiang Zhang, Jun Zhou, Lanning Wei, Da Zheng, Haofen Wang, Huajun Chen:
OneKE: A Dockerized Schema-Guided LLM Agent-based Knowledge Extraction System. CoRR abs/2412.20005 (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) - [c164]Yi-Xuan Sun, Ya-Lin Zhang, Wei Wang, Longfei Li, Jun Zhou:
Treatment Effect Estimation across Domains. CIKM 2023: 2352-2361 - [c163]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 - [c162]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 - [c161]Lu Yu, Meng Li, Ya-Lin Zhang, Longfei Li, Jun Zhou:
FINRule: Feature Interactive Neural Rule Learning. CIKM 2023: 3020-3029 - [c160]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 - [c159]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 - [c158]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 - [c157]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 - [c156]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 - [c155]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 - [c154]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 - [c153]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 - [c152]Gangwei Jiang, Caigao Jiang, Siqiao Xue, James Zhang, Jun Zhou, Defu Lian, Ying Wei:
Towards Anytime Fine-tuning: Continually Pre-trained Language Models with Hypernetwork Prompts. EMNLP (Findings) 2023: 12081-12095 - [c151]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 - [c150]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 - [c149]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 - [c148]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 - [c147]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 - [c146]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. ICDM (Workshops) 2023: 588-592 - [c145]Kaituo Feng, Changsheng Li, Xiaolu Zhang, Jun Zhou:
Towards Open Temporal Graph Neural Networks. ICLR 2023 - [c144]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 - [c143]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 - [c142]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 - [c141]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 - [c140]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 - [c139]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 - [c138]Jia Gu, Caizhi Tang, Han Yan, Qing Cui, Longfei Li, Jun Zhou:
FAST: a Fused and Accurate Shrinkage Tree for Heterogeneous Treatment Effects Estimation. NeurIPS 2023 - [c137]Xiaoming Shi, Siqiao Xue, Kangrui Wang, Fan Zhou, James Y. Zhang, Jun Zhou, Chenhao Tan, Hongyuan Mei:
Language Models Can Improve Event Prediction by Few-Shot Abductive Reasoning. NeurIPS 2023 - [c136]Yongduo Sui, Qitian Wu, Jiancan Wu, Qing Cui, Longfei Li, Jun Zhou, Xiang Wang, Xiangnan He:
Unleashing the Power of Graph Data Augmentation on Covariate Distribution Shift. NeurIPS 2023 - [c135]Siqiao Xue, Yan Wang, Zhixuan Chu, Xiaoming Shi, Caigao Jiang, Hongyan Hao, Gangwei Jiang, Xiaoyun Feng, James Zhang, Jun Zhou:
Prompt-augmented Temporal Point Process for Streaming Event Sequence. NeurIPS 2023 - [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 - [i93]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) - [i92]Lei Chen, Le Wu, Kun Zhang, Richang Hong, Defu Lian, Zhiqiang Zhang, Jun Zhou, Meng Wang:
Improving Recommendation Fairness via Data Augmentation. CoRR abs/2302.06333 (2023) - [i91]Kaituo Feng, Changsheng Li, Xiaolu Zhang, Jun Zhou:
Towards Open Temporal Graph Neural Networks. CoRR abs/2303.15015 (2023) - [i90]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) - [i89]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) - [i88]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) - [i87]Xiaoming Shi, Siqiao Xue, Kangrui Wang, Fan Zhou, James Y. Zhang, Jun Zhou, Chenhao Tan, Hongyuan Mei:
Language Models Can Improve Event Prediction by Few-Shot Abductive Reasoning. CoRR abs/2305.16646 (2023) - [i86]Kun Zhang, Le Wu, Guangyi Lv, Enhong Chen, Shulan Ruan, Jing Liu, Zhiqiang Zhang, Jun Zhou, Meng Wang:
Description-Enhanced Label Embedding Contrastive Learning for Text Classification. CoRR abs/2306.08817 (2023) - [i85]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) - [i84]Yonghui Yang, Zhengwei Wu, Le Wu, Kun Zhang, Richang Hong, Zhiqiang Zhang, Jun Zhou, Meng Wang:
Generative Contrastive Graph Learning for Recommendation. CoRR abs/2307.05100 (2023) - [i83]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) - [i82]Chaochao Chen, Xiaohua Feng, Jun Zhou, Jianwei Yin, Xiaolin Zheng:
Federated Large Language Model: A Position Paper. CoRR abs/2307.08925 (2023) - [i81]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) - [i80]Siqiao Xue, Fan Zhou, Yi Xu, Hongyu Zhao, Shuo Xie, Qingyang Dai, Caigao Jiang, James Y. Zhang, Jun Zhou, Dacheng Xiu, Hongyuan Mei:
WeaverBird: Empowering Financial Decision-Making with Large Language Model, Knowledge Base, and Search Engine. CoRR abs/2308.05361 (2023) - [i79]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) - [i78]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) - [i77]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) - [i76]Qian Zhao, Zhengwei Wu, Zhiqiang Zhang, Jun Zhou:
Long-tail Augmented Graph Contrastive Learning for Recommendation. CoRR abs/2309.11177 (2023) - [i75]Siqiao Xue, Yan Wang, Zhixuan Chu, Xiaoming Shi, Caigao Jiang, Hongyan Hao, Gangwei Jiang, Xiaoyun Feng, James Y. Zhang, Jun Zhou:
Prompt-augmented Temporal Point Process for Streaming Event Sequence. CoRR abs/2310.04993 (2023) - [i74]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) - [i73]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) - [i72]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) - [i71]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) - [i70]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) - [i69]Chunjing Gan, Bo Huang, Binbin Hu, Jian Ma, Ziqi Liu, Zhiqiang Zhang, Jun Zhou, Guannan Zhang, Wenliang Zhong:
PEACE: Prototype lEarning Augmented transferable framework for Cross-domain rEcommendation. CoRR abs/2312.01916 (2023) - [i68]Yakun Wang, Binbin Hu, Shuo Yang, Meiqi Zhu, Zhiqiang Zhang, Qiyang Zhang, Jun Zhou, Guo Ye, Huimei He:
Not All Negatives Are Worth Attending to: Meta-Bootstrapping Negative Sampling Framework for Link Prediction. CoRR abs/2312.04815 (2023) - [i67]Chunjing Gan, Dan Yang, Binbin Hu, Ziqi Liu, Yue Shen, Zhiqiang Zhang, Jinjie Gu, Jun Zhou, Guannan Zhang:
Making Large Language Models Better Knowledge Miners for Online Marketing with Progressive Prompting Augmentation. CoRR abs/2312.05276 (2023) - [i66]Youshao Xiao, Weichang Wu, Zhenglei Zhou, Fagui Mao, Shangchun Zhao, Lin Ju, Lei Liang, Xiaolu Zhang, Jun Zhou:
An Adaptive Placement and Parallelism Framework for Accelerating RLHF Training. CoRR abs/2312.11819 (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 - [i65]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) - [i64]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) - [i63]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) - [i62]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) - [i61]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) - [i60]Binbin Hu, Zhiyang Hu, Zhiqiang Zhang, Jun Zhou, Chuan Shi:
KGNN: Distributed Framework for Graph Neural Knowledge Representation. CoRR abs/2205.08285 (2022) - [i59]Shih-Han Chan, Yinpeng Dong, Jun Zhu, Xiaolu Zhang, Jun Zhou:
BadDet: Backdoor Attacks on Object Detection. CoRR abs/2205.14497 (2022) - [i58]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. CoRR abs/2207.13329 (2022) - [i57]Shujie Yang, Binchi Zhang, Shangbin Feng, Zhaoxuan Tan, Qinghua Zheng, Jun Zhou, Minnan Luo:
AHEAD: A Triple Attention Based Heterogeneous Graph Anomaly Detection Approach. CoRR abs/2208.08200 (2022) - [i56]Xinshun Feng, Herun Wan, Shangbin Feng, Hongrui Wang, Jun Zhou, Qinghua Zheng, Minnan Luo:
GraTO: Graph Neural Network Framework Tackling Over-smoothing with Neural Architecture Search. CoRR abs/2208.09027 (2022) - [i55]Jun Zhou, Feng Qi, Zhigang Hua, Daohong Jian, Ziqi Liu, Hua Wu, Xingwen Zhang, Shuang Yang:
A Practical Distributed ADMM Solver for Billion-Scale Generalized Assignment Problems. CoRR abs/2210.16986 (2022) - [i54]Xinyu Li, Yilin Li, Qing Cui, Longfei Li, Jun Zhou:
Robust Direct Learning for Causal Data Fusion. CoRR abs/2211.00249 (2022) - 2021
- [j6]Jun Zhou, Longfei Li, Ziqi Liu, Chaochao Chen:
A Boosting Framework of Factorization Machine. Int. J. Pattern Recognit. Artif. Intell. 35(10): 2159036:1-2159036:20 (2021) - [j5]Longfei Zheng, Jun Zhou, Chaochao Chen, Bingzhe Wu, Li Wang, Benyu Zhang:
ASFGNN: Automated separated-federated graph neural network. Peer-to-Peer Netw. Appl. 14(3): 1692-1704 (2021) - [c72]Qianyu Yu, Shuo Yang, Zhiqiang Zhang, Ya-Lin Zhang, Binbin Hu, Ziqi Liu, Kai Huang, Xingyu Zhong, Jun Zhou, Yanming Fang:
A Graph Attention Network Model for GMV Forecast on Online Shopping Festival. APWeb/WAIM (1) 2021: 134-139 - [c71]Wenjing Fang, Derun Zhao, Jin Tan, Chaochao Chen, Chaofan Yu, Li Wang, Lei Wang, Jun Zhou, Benyu Zhang:
Large-scale Secure XGB for Vertical Federated Learning. CIKM 2021: 443-452 - [c70]Ke Tu, Peng Cui, Daixin Wang, Zhiqiang Zhang, Jun Zhou, Yuan Qi, Wenwu Zhu:
Conditional Graph Attention Networks for Distilling and Refining Knowledge Graphs in Recommendation. CIKM 2021: 1834-1843 - [c69]Kun Xiong, Wenwen Ye, Xu Chen, Yongfeng Zhang, Wayne Xin Zhao, Binbin Hu, Zhiqiang Zhang, Jun Zhou:
Counterfactual Review-based Recommendation. CIKM 2021: 2231-2240 - [c68]Ziqi Liu, Yue Shen, Xiaocheng Cheng, Qiang Li, Jianping Wei, Zhiqiang Zhang, Dong Wang, Xiaodong Zeng, Jinjie Gu, Jun Zhou:
Learning Representations of Inactive Users: A Cross Domain Approach with Graph Neural Networks. CIKM 2021: 3278-3282 - [c67]Tianxin Wang, Fuzhen Zhuang, Zhiqiang Zhang, Daixin Wang, Jun Zhou, Qing He:
Low-dimensional Alignment for Cross-Domain Recommendation. CIKM 2021: 3508-3512 - [c66]Kai Zhang, Hao Qian, Qi Liu, Zhiqiang Zhang, Jun Zhou, Jianhui Ma, Enhong Chen:
SIFN: A Sentiment-aware Interactive Fusion Network for Review-based Item Recommendation. CIKM 2021: 3627-3631 - [c65]Jun Zhou, Yang Bao, Hua Wu, Zhigang Hua:
AntOpt: A Multi-functional Large-scale Decision Optimization Platform. CIKM 2021: 4833-4837 - [c64]Zihao Xiao, Xianfeng Gao, Chilin Fu, Yinpeng Dong, Wei Gao, Xiaolu Zhang, Jun Zhou, Jun Zhu:
Improving Transferability of Adversarial Patches on Face Recognition With Generative Models. CVPR 2021: 11845-11854 - [c63]Meng Li, Ya-Lin Zhang, Qitao Shi, Xinxing Yang, Qing Cui, Longfei Li, Jun Zhou:
Constraint-Adaptive Rule Mining in Large Databases. DASFAA (3) 2021: 579-591 - [c62]Minghui Yang, Shaosheng Cao, Binbin Hu, Xianling Chen, Hengbin Cui, Zhiqiang Zhang, Jun Zhou, Xiaolong Li:
IntelliTag: An Intelligent Cloud Customer Service System Based on Tag Recommendation. ICDE 2021: 2559-2570 - [c61]Yankun Ren, Longfei Li, Jun Zhou:
Simtrojan: Stealthy Backdoor Attack. ICIP 2021: 819-823 - [c60]Yulong Wang, Xiaolu Zhang, Jun Zhou, Hang Su:
Rethinking the Effectiveness of Selective Attention in Neural Networks. ICONIP (3) 2021: 532-543 - [c59]Feng Zhu, Yan Wang, Chaochao Chen, Jun Zhou, Longfei Li, Guanfeng Liu:
Cross-Domain Recommendation: Challenges, Progress, and Prospects. IJCAI 2021: 4721-4728 - [c58]Ya-Lin Zhang, Qitao Shi, Meng Li, Xinxing Yang, Longfei Li, Jun Zhou:
A Classification Based Ensemble Pruning Framework with Multi-metric Consideration. IntelliSys (1) 2021: 650-667 - [c57]Chaochao Chen, Jun Zhou, Li Wang, Xibin Wu, Wenjing Fang, Jin Tan, Lei Wang, Alex X. Liu, Hao Wang, Cheng Hong:
When Homomorphic Encryption Marries Secret Sharing: Secure Large-Scale Sparse Logistic Regression and Applications in Risk Control. KDD 2021: 2652-2662 - [c56]Zhibo Zhu, Ziqi Liu, Ge Jin, Zhiqiang Zhang, Lei Chen, Jun Zhou, Jianyong Zhou:
MixSeq: Connecting Macroscopic Time Series Forecasting with Microscopic Time Series Data. NeurIPS 2021: 12904-12916 - [c55]Runzhong Wang, Zhigang Hua, Gan Liu, Jiayi Zhang, Junchi Yan, Feng Qi, Shuang Yang, Jun Zhou, Xiaokang Yang:
A Bi-Level Framework for Learning to Solve Combinatorial Optimization on Graphs. NeurIPS 2021: 21453-21466 - [c54]Shuo Yang, Binbin Hu, Zhiqiang Zhang, Wang Sun, Yang Wang, Jun Zhou, Hongyu Shan, Yuetian Cao, Borui Ye, Yanming Fang, Quan Yu:
Inductive Link Prediction with Interactive Structure Learning on Attributed Graph. ECML/PKDD (2) 2021: 383-398 - [c53]Daixin Wang, Zhiqiang Zhang, Jun Zhou, Peng Cui, Jingli Fang, Quanhui Jia, Yanming Fang, Yuan Qi:
Temporal-Aware Graph Neural Network for Credit Risk Prediction. SDM 2021: 702-710 - [c52]Zhaoxin Huan, Yulong Wang, Yong He, Xiaolu Zhang, Chilin Fu, Weichang Wu, Jun Zhou, Ke Ding, Liang Zhang, Linjian Mo:
Learning to Select Instance: Simultaneous Transfer Learning and Clustering. SIGIR 2021: 1950-1954 - [c51]Kai Zhang, Hao Qian, Qing Cui, Qi Liu, Longfei Li, Jun Zhou, Jianhui Ma, Enhong Chen:
Multi-Interactive Attention Network for Fine-grained Feature Learning in CTR Prediction. WSDM 2021: 984-992 - [i53]Feng Zhu, Yan Wang, Chaochao Chen, Jun Zhou, Longfei Li, Guanfeng Liu:
Cross-Domain Recommendation: Challenges, Progress, and Prospects. CoRR abs/2103.01696 (2021) - [i52]Runzhong Wang, Zhigang Hua, Gan Liu, Jiayi Zhang, Junchi Yan, Feng Qi, Shuang Yang, Jun Zhou, Xiaokang Yang:
A Bi-Level Framework for Learning to Solve Combinatorial Optimization on Graphs. CoRR abs/2106.04927 (2021) - [i51]Zihao Xiao, Xianfeng Gao, Chilin Fu, Yinpeng Dong, Wei Gao, Xiaolu Zhang, Jun Zhou, Jun Zhu:
Improving Transferability of Adversarial Patches on Face Recognition with Generative Models. CoRR abs/2106.15058 (2021) - [i50]Feng Zhu, Yan Wang, Jun Zhou, Chaochao Chen, Longfei Li, Guanfeng Liu:
A Unified Framework for Cross-Domain and Cross-System Recommendations. CoRR abs/2108.07976 (2021) - [i49]Kai Zhang, Hao Qian, Qi Liu, Zhiqiang Zhang, Jun Zhou, Jianhui Ma, Enhong Chen:
SIFN: A Sentiment-aware Interactive Fusion Network for Review-based Item Recommendation. CoRR abs/2108.08022 (2021) - [i48]Binchi Zhang, Minnan Luo, Shangbin Feng, Ziqi Liu, Jun Zhou, Qinghua Zheng:
PPSGCN: A Privacy-Preserving Subgraph Sampling Based Distributed GCN Training Method. CoRR abs/2110.12906 (2021) - [i47]Zhibo Zhu, Ziqi Liu, Ge Jin, Zhiqiang Zhang, Lei Chen, Jun Zhou, Jianyong Zhou:
MixSeq: Connecting Macroscopic Time Series Forecasting with Microscopic Time Series Data. CoRR abs/2110.14354 (2021) - [i46]Ke Tu, Peng Cui, Daixin Wang, Zhiqiang Zhang, Jun Zhou, Yuan Qi, Wenwu Zhu:
Conditional Attention Networks for Distilling Knowledge Graphs in Recommendation. CoRR abs/2111.02100 (2021) - [i45]Boxin Zhao, Ziqi Liu, Chaochao Chen, Mladen Kolar, Zhiqiang Zhang, Jun Zhou:
Adaptive Client Sampling in Federated Learning via Online Learning with Bandit Feedback. CoRR abs/2112.14332 (2021) - 2020
- [j4]Dalong Zhang, Xin Huang, Ziqi Liu, Jun Zhou, Zhiyang Hu, Xianzheng Song, Zhibang Ge, Lin Wang, Zhiqiang Zhang, Yuan Qi:
AGL: A Scalable System for Industrial-purpose Graph Machine Learning. Proc. VLDB Endow. 13(12): 3125-3137 (2020) - [j3]Chaochao Chen, Jun Zhou, Bingzhe Wu, Wenjing Fang, Li Wang, Yuan Qi, Xiaolin Zheng:
Practical Privacy Preserving POI Recommendation. ACM Trans. Intell. Syst. Technol. 11(5): 52:1-52:20 (2020) - [c50]Bingzhe Wu, Chaochao Chen, Shiwan Zhao, Cen Chen, Yuan Yao, Guangyu Sun, Li Wang, Xiaolu Zhang, Jun Zhou:
Characterizing Membership Privacy in Stochastic Gradient Langevin Dynamics. AAAI 2020: 6372-6379 - [c49]Yulong Wang, Xiaolu Zhang, Lingxi Xie, Jun Zhou, Hang Su, Bo Zhang, Xiaolin Hu:
Pruning from Scratch. AAAI 2020: 12273-12280 - [c48]Binbin Hu, Zhiqiang Zhang, Jun Zhou, Jingli Fang, Quanhui Jia, Yanming Fang, Quan Yu, Yuan Qi:
Loan Default Analysis with Multiplex Graph Learning. CIKM 2020: 2525-2532 - [c47]Kuan Xu, Chilin Fu, Xiaolu Zhang, Cen Chen, Ya-Lin Zhang, Wenge Rong, Zujie Wen, Jun Zhou, Xiaolong Li, Yu Qiao:
aDMSCN: A Novel Perspective for User Intent Prediction in Customer Service Bots. CIKM 2020: 2853-2860 - [c46]Cen Chen, Bingzhe Wu, Li Wang, Chaochao Chen, Jin Tan, Lei Wang, Jun Zhou, Benyu Zhang:
Nebula: A Scalable Privacy-Preserving Machine Learning System in Ant Financial. CIKM 2020: 3369-3372 - [c45]Zhiqiang Zhang, Jun Zhou, Chuan Shi:
EasyGML: A Fully-functional and Easy-to-use Platform for Industrial Graph Machine Learning. CIKM 2020: 3485-3488 - [c44]Chaochao Chen, Liang Li, Bingzhe Wu, Cheng Hong, Li Wang, Jun Zhou:
Secure Social Recommendation Based on Secret Sharing. ECAI 2020: 506-512 - [c43]Yankun Ren, Jianbin Lin, Siliang Tang, Jun Zhou, Shuang Yang, Yuan Qi, Xiang Ren:
Generating Natural Language Adversarial Examples on a Large Scale with Generative Models. ECAI 2020: 2156-2163 - [c42]Qitao Shi, Ya-Lin Zhang, Longfei Li, Xinxing Yang, Meng Li, Jun Zhou:
SAFE: Scalable Automatic Feature Engineering Framework for Industrial Tasks. ICDE 2020: 1645-1656 - [c41]Shuo Yang, Zhiqiang Zhang, Jun Zhou, Yang Wang, Wang Sun, Xingyu Zhong, Yanming Fang, Quan Yu, Yuan Qi:
Financial Risk Analysis for SMEs with Graph-based Supply Chain Mining. IJCAI 2020: 4661-4667 - [c40]Chenyi Zhuang, Ziqi Liu, Zhiqiang Zhang, Yize Tan, Zhengwei Wu, Zhining Liu, Jianping Wei, Jinjie Gu, Guannan Zhang, Jun Zhou, Yuan Qi:
Hubble: An Industrial System for Audience Expansion in Mobile Marketing. KDD 2020: 2455-2463 - [c39]Ziqi Liu, Zhengwei Wu, Zhiqiang Zhang, Jun Zhou, Shuang Yang, Le Song, Yuan Qi:
Bandit Samplers for Training Graph Neural Networks. NeurIPS 2020 - [c38]Zhaoxin Huan, Yulong Wang, Xiaolu Zhang, Lin Shang, Chilin Fu, Jun Zhou:
Data-Free Adversarial Perturbations for Practical Black-Box Attack. PAKDD (2) 2020: 127-138 - [c37]Qing Cui, Qitao Shi, Hao Qian, Caizhi Tang, Xixi Li, Yiming Zhao, Tao Jiang, Longfei Li, Jun Zhou:
AutoRec: A Comprehensive Platform for Building Effective and Explainable Recommender Models. ECML/PKDD (5) 2020: 541-545 - [c36]Cen Chen, Ya-Lin Zhang, Minghui Qiu, Bingzhe Wu, Li Wang, Longfei Li, Jun Zhou:
Automatic Knowledge Fusion in Transferrable Networks for Semantic Text Matching. WWW (Companion Volume) 2020: 73-74 - [c35]Yankun Ren, Jianbin Lin, Jun Zhou:
Neural Zero-Shot Fine-Grained Entity Typing. WWW (Companion Volume) 2020: 846-847 - [i44]Chaochao Chen, Liang Li, Bingzhe Wu, Cheng Hong, Li Wang, Jun Zhou:
Secure Social Recommendation based on Secret Sharing. CoRR abs/2002.02088 (2020) - [i43]Yingting Liu, Chaochao Chen, Longfei Zheng, Li Wang, Jun Zhou, Guiquan Liu:
Privacy Preserving PCA for Multiparty Modeling. CoRR abs/2002.02091 (2020) - [i42]Chaochao Chen, Ziqi Liu, Jun Zhou, Xiaolong Li, Yuan Qi, Yujing Jiao, Xingyu Zhong:
How Much Can A Retailer Sell? Sales Forecasting on Tmall. CoRR abs/2002.11940 (2020) - [i41]Wenjing Fang, Chaochao Chen, Bowen Song, Li Wang, Jun Zhou, Kenny Q. Zhu:
Adapted tree boosting for Transfer Learning. CoRR abs/2002.11982 (2020) - [i40]Dalong Zhang, Xianzheng Song, Ziqi Liu, Zhiqiang Zhang, Xin Huang, Lin Wang, Jun Zhou:
DSSLP: A Distributed Framework for Semi-supervised Link Prediction. CoRR abs/2002.12056 (2020) - [i39]Ziqi Liu, Chaochao Chen, Xinxing Yang, Jun Zhou, Xiaolong Li, Le Song:
Heterogeneous Graph Neural Networks for Malicious Account Detection. CoRR abs/2002.12307 (2020) - [i38]Chen Liang, Ziqi Liu, Bin Liu, Jun Zhou, Xiaolong Li, Shuang Yang, Yuan Qi:
Uncovering Insurance Fraud Conspiracy with Network Learning. CoRR abs/2002.12789 (2020) - [i37]Daixin Wang, Jianbin Lin, Peng Cui, Quanhui Jia, Zhen Wang, Yanming Fang, Quan Yu, Jun Zhou, Shuang Yang, Yuan Qi:
A Semi-supervised Graph Attentive Network for Financial Fraud Detection. CoRR abs/2003.01171 (2020) - [i36]Zhaoxin Huan, Yulong Wang, Xiaolu Zhang, Lin Shang, Chilin Fu, Jun Zhou:
Data-Free Adversarial Perturbations for Practical Black-Box Attack. CoRR abs/2003.01295 (2020) - [i35]Ziqi Liu, Dong Wang, Qianyu Yu, Zhiqiang Zhang, Yue Shen, Jian Ma, Wenliang Zhong, Jinjie Gu, Jun Zhou, Shuang Yang, Yuan Qi:
Graph Representation Learning for Merchant Incentive Optimization in Mobile Payment Marketing. CoRR abs/2003.01515 (2020) - [i34]Dalong Zhang, Xin Huang, Ziqi Liu, Zhiyang Hu, Xianzheng Song, Zhibang Ge, Zhiqiang Zhang, Lin Wang, Jun Zhou, Shuang Yang, Yuan Qi:
AGL: a Scalable System for Industrial-purpose Graph Machine Learning. CoRR abs/2003.02454 (2020) - [i33]Qitao Shi, Ya-Lin Zhang, Longfei Li, Xinxing Yang, Meng Li, Jun Zhou:
SAFE: Scalable Automatic Feature Engineering Framework for Industrial Tasks. CoRR abs/2003.02556 (2020) - [i32]Cen Chen, Chen Liang, Jianbin Lin, Li Wang, Ziqi Liu, Xinxing Yang, Xiukun Wang, Jun Zhou, Shuang Yang, Yuan Qi:
InfDetect: a Large Scale Graph-based Fraud Detection System for E-Commerce Insurance. CoRR abs/2003.02833 (2020) - [i31]Chaochao Chen, Bingzhe Wu, Wenjin Fang, Jun Zhou, Li Wang, Yuan Qi, Xiaolin Zheng:
Practical Privacy Preserving POI Recommendation. CoRR abs/2003.02834 (2020) - [i30]Longfei Zheng, Chaochao Chen, Yingting Liu, Bingzhe Wu, Xibin Wu, Li Wang, Lei Wang, Jun Zhou, Shuang Yang:
Industrial Scale Privacy Preserving Deep Neural Network. CoRR abs/2003.05198 (2020) - [i29]Chaochao Chen, Ziqi Liu, Peilin Zhao, Jun Zhou, Xiaolong Li:
Privacy Preserving Point-of-interest Recommendation Using Decentralized Matrix Factorization. CoRR abs/2003.05610 (2020) - [i28]Jianbin Lin, Daixin Wang, Lu Guan, Yin Zhao, Binqiang Zhao, Jun Zhou, Xiaolong Li, Yuan Qi:
RNE: A Scalable Network Embedding for Billion-scale Recommendation. CoRR abs/2003.07158 (2020) - [i27]Yankun Ren, Jianbin Lin, Siliang Tang, Jun Zhou, Shuang Yang, Yuan Qi, Xiang Ren:
Generating Natural Language Adversarial Examples on a Large Scale with Generative Models. CoRR abs/2003.10388 (2020) - [i26]Jianbin Lin, Zhiqiang Zhang, Jun Zhou, Xiaolong Li, Jingli Fang, Yanming Fang, Quan Yu, Yuan Qi:
NetDP: An Industrial-Scale Distributed Network Representation Framework for Default Prediction in Ant Credit Pay. CoRR abs/2004.00201 (2020) - [i25]Wenjing Fang, Jun Zhou, Xiaolong Li, Kenny Q. Zhu:
Unpack Local Model Interpretation for GBDT. CoRR abs/2004.01358 (2020) - [i24]Chaochao Chen, Liang Li, Wenjing Fang, Jun Zhou, Li Wang, Lei Wang, Shuang Yang, Alex Liu, Hao Wang:
Secret Sharing based Secure Regressions with Applications. CoRR abs/2004.04898 (2020) - [i23]Wenjing Fang, Chaochao Chen, Jin Tan, Chaofan Yu, Yufei Lu, Li Wang, Lei Wang, Jun Zhou, Alex X:
A Hybrid-Domain Framework for Secure Gradient Tree Boosting. CoRR abs/2005.08479 (2020) - [i22]Jun Zhou, Chaochao Chen, Longfei Zheng, Xiaolin Zheng, Bingzhe Wu, Ziqi Liu, Li Wang:
Privacy-Preserving Graph Neural Network for Node Classification. CoRR abs/2005.11903 (2020) - [i21]Ziqi Liu, Zhengwei Wu, Zhiqiang Zhang, Jun Zhou, Shuang Yang, Le Song, Yuan Qi:
Bandit Samplers for Training Graph Neural Networks. CoRR abs/2006.05806 (2020) - [i20]Chaochao Chen, Jun Zhou, Li Wang, Xibin Wu, Wenjing Fang, Jin Tan, Lei Wang, Xiaoxi Ji, Alex Liu, Hao Wang, Cheng Hong:
When Homomorphic Encryption Marries Secret Sharing: Secure Large-Scale Sparse Logistic Regression and Applications in Risk Control. CoRR abs/2008.08753 (2020) - [i19]Jinghan Shi, Houye Ji, Chuan Shi, Xiao Wang, Zhiqiang Zhang, Jun Zhou:
Heterogeneous Graph Neural Network for Recommendation. CoRR abs/2009.00799 (2020) - [i18]Lu Yu, Shichao Pei, Chuxu Zhang, Lizhong Ding, Jun Zhou, Longfei Li, Xiangliang Zhang:
Self-supervised Smoothing Graph Neural Networks. CoRR abs/2009.00934 (2020) - [i17]Cen Chen, Bingzhe Wu, Minghui Qiu, Li Wang, Jun Zhou:
A Comprehensive Analysis of Information Leakage in Deep Transfer Learning. CoRR abs/2009.01989 (2020) - [i16]Longfei Zheng, Jun Zhou, Chaochao Chen, Bingzhe Wu, Li Wang, Benyu Zhang:
ASFGNN: Automated Separated-Federated Graph Neural Network. CoRR abs/2011.03248 (2020) - [i15]Kai Zhang, Hao Qian, Qing Cui, Qi Liu, Longfei Li, Jun Zhou, Jianhui Ma, Enhong Chen:
Multi-Interactive Attention Network for Fine-grained Feature Learning in CTR Prediction. CoRR abs/2012.06968 (2020) - [i14]Chaochao Chen, Jun Zhou, Longfei Zheng, Yan Wang, Xiaolin Zheng, Bingzhe Wu, Cen Chen, Li Wang, Jianwei Yin:
Towards Scalable and Privacy-Preserving Deep Neural Network via Algorithmic-Cryptographic Co-design. CoRR abs/2012.09364 (2020)
2010 – 2019
- 2019
- [j2]Shaosheng Cao, Xinxing Yang, Cen Chen, Jun Zhou, Xiaolong Li, Yuan Qi:
TitAnt: Online Real-time Transaction Fraud Detection in Ant Financial. Proc. VLDB Endow. 12(12): 2082-2093 (2019) - [j1]Ya-Lin Zhang, Jun Zhou, Wenhao Zheng, Ji Feng, Longfei Li, Ziqi Liu, Ming Li, Zhiqiang Zhang, Chaochao Chen, Xiaolong Li, Yuan (Alan) Qi, Zhi-Hua Zhou:
Distributed Deep Forest and its Application to Automatic Detection of Cash-Out Fraud. ACM Trans. Intell. Syst. Technol. 10(5): 55:1-55:19 (2019) - [c34]Binbin Hu, Zhiqiang Zhang, Chuan Shi, Jun Zhou, Xiaolong Li, Yuan Qi:
Cash-Out User Detection Based on Attributed Heterogeneous Information Network with a Hierarchical Attention Mechanism. AAAI 2019: 946-953 - [c33]Ziqi Liu, Chaochao Chen, Longfei Li, Jun Zhou, Xiaolong Li, Le Song, Yuan Qi:
GeniePath: Graph Neural Networks with Adaptive Receptive Paths. AAAI 2019: 4424-4431 - [c32]Wenjing Fang, Chaochao Chen, Bowen Song, Li Wang, Jun Zhou, Kenny Q. Zhu:
Adapted Tree Boosting for Transfer Learning. IEEE BigData 2019: 741-750 - [c31]Dalong Zhang, Xianzheng Song, Ziqi Liu, Zhiqiang Zhang, Xin Huang, Lin Wang, Jun Zhou:
DSSLP: A Distributed Framework for Semi-supervised Link Prediction. IEEE BigData 2019: 1557-1566 - [c30]Cen Chen, Chen Liang, Jianbin Lin, Li Wang, Ziqi Liu, Xinxing Yang, Jun Zhou, Shuang Yang, Yuan Qi:
InfDetect: a Large Scale Graph-based Fraud Detection System for E-Commerce Insurance. IEEE BigData 2019: 1765-1773 - [c29]Ziqi Liu, Dong Wang, Qianyu Yu, Zhiqiang Zhang, Yue Shen, Jian Ma, Wenliang Zhong, Jinjie Gu, Jun Zhou, Shuang Yang, Yuan Qi:
Graph Representation Learning for Merchant Incentive Optimization in Mobile Payment Marketing. CIKM 2019: 2577-2584 - [c28]Daixin Wang, Yuan Qi, Jianbin Lin, Peng Cui, Quanhui Jia, Zhen Wang, Yanming Fang, Quan Yu, Jun Zhou, Shuang Yang:
A Semi-Supervised Graph Attentive Network for Financial Fraud Detection. ICDM 2019: 598-607 - [c27]Cen Chen, Xiaolu Zhang, Sheng Ju, Chilin Fu, Caizhi Tang, Jun Zhou, Xiaolong Li:
AntProphet: an Intention Mining System behind Alipay's Intelligent Customer Service Bot. IJCAI 2019: 6497-6499 - [c26]Bingzhe Wu, Shiwan Zhao, Chaochao Chen, Haoyang Xu, Li Wang, Xiaolu Zhang, Guangyu Sun, Jun Zhou:
Generalization in Generative Adversarial Networks: A Novel Perspective from Privacy Protection. NeurIPS 2019: 306-316 - [c25]Chaochao Chen, Ziqi Liu, Jun Zhou, Xiaolong Li, Yuan Qi, Yujing Jiao, Xingyu Zhong:
How Much Can A Retailer Sell? Sales Forecasting on Tmall. PAKDD (2) 2019: 204-216 - [c24]Jianbin Lin, Daixin Wang, Lu Guan, Yin Zhao, Binqiang Zhao, Jun Zhou, Xiaolong Li, Yuan (Alan) Qi:
RNE: A Scalable Network Embedding for Billion-Scale Recommendation. PAKDD (2) 2019: 432-445 - [c23]Chen Liang, Ziqi Liu, Bin Liu, Jun Zhou, Xiaolong Li, Shuang Yang, Yuan Qi:
Uncovering Insurance Fraud Conspiracy with Network Learning. SIGIR 2019: 1181-1184 - [c22]Cen Chen, Chilin Fu, Xu Hu, Xiaolu Zhang, Jun Zhou, Xiaolong Li, Forrest Sheng Bao:
Reinforcement Learning for User Intent Prediction in Customer Service Bots. SIGIR 2019: 1265-1268 - [c21]Cen Chen, Minghui Qiu, Yinfei Yang, Jun Zhou, Jun Huang, Xiaolong Li, Forrest Sheng Bao:
Multi-Domain Gated CNN for Review Helpfulness Prediction. WWW 2019: 2630-2636 - [i13]Shaosheng Cao, Xinxing Yang, Cen Chen, Jun Zhou, Xiaolong Li, Yuan (Alan) Qi:
TitAnt: Online Real-time Transaction Fraud Detection in Ant Financial. CoRR abs/1906.07407 (2019) - [i12]Bingzhe Wu, Shiwan Zhao, Haoyang Xu, Chaochao Chen, Li Wang, Xiaolu Zhang, Guangyu Sun, Jun Zhou:
Generalization in Generative Adversarial Networks: A Novel Perspective from Privacy Protection. CoRR abs/1908.07882 (2019) - [i11]Yulong Wang, Xiaolu Zhang, Lingxi Xie, Jun Zhou, Hang Su, Bo Zhang, Xiaolin Hu:
Pruning from Scratch. CoRR abs/1909.12579 (2019) - [i10]Bingzhe Wu, Chaochao Chen, Shiwan Zhao, Cen Chen, Yuan Yao, Guangyu Sun, Li Wang, Xiaolu Zhang, Jun Zhou:
Characterizing Membership Privacy in Stochastic Gradient Langevin Dynamics. CoRR abs/1910.02249 (2019) - [i9]Longfei Li, Ziqi Liu, Chaochao Chen, Ya-Lin Zhang, Jun Zhou, Xiaolong Li:
A Time Attention based Fraud Transaction Detection Framework. CoRR abs/1912.11760 (2019) - 2018
- [c20]Chaochao Chen, Ziqi Liu, Peilin Zhao, Jun Zhou, Xiaolong Li:
Privacy Preserving Point-of-Interest Recommendation Using Decentralized Matrix Factorization. AAAI 2018: 257-264 - [c19]Shaosheng Cao, Wei Lu, Jun Zhou, Xiaolong Li:
cw2vec: Learning Chinese Word Embeddings with Stroke n-gram Information. AAAI 2018: 5053-5061 - [c18]Jianbin Lin, Zhiqiang Zhang, Jun Zhou, Xiaolong Li, Jingli Fang, Yanming Fang, Quan Yu, Yuan (Alan) Qi:
NetDP: An Industrial-Scale Distributed Network Representation Framework for Default Prediction in Ant Credit Pay. IEEE BigData 2018: 1960-1965 - [c17]Ziqi Liu, Chaochao Chen, Xinxing Yang, Jun Zhou, Xiaolong Li, Le Song:
Heterogeneous Graph Neural Networks for Malicious Account Detection. CIKM 2018: 2077-2085 - [c16]Zhiqiang Zhang, Chaochao Chen, Jun Zhou, Xiaolong Li:
An Industrial-Scale System for Heterogeneous Information Card Ranking in Alipay. DASFAA (2) 2018: 713-724 - [c15]Wenjing Fang, Jun Zhou, Xiaolong Li, Kenny Q. Zhu:
Unpack Local Model Interpretation for GBDT. DASFAA (2) 2018: 764-775 - [c14]Chaochao Chen, Ziqi Liu, Peilin Zhao, Longfei Li, Jun Zhou, Xiaolong Li:
Distributed Collaborative Hashing and Its Applications in Ant Financial. KDD 2018: 100-109 - [c13]Cen Chen, Yinfei Yang, Jun Zhou, Xiaolong Li, Forrest Sheng Bao:
Cross-Domain Review Helpfulness Prediction Based on Convolutional Neural Networks with Auxiliary Domain Discriminators. NAACL-HLT (2) 2018: 602-607 - [c12]Xinxing Yang, Jun Zhou, Peilin Zhao, Cen Chen, Chaochao Chen, Xiaolong Li:
A Local Online Learning Approach for Non-linear Data. PAKDD (2) 2018: 431-443 - [c11]Ya-Lin Zhang, Longfei Li, Jun Zhou, Xiaolong Li, Zhi-Hua Zhou:
Anomaly Detection with Partially Observed Anomalies. WWW (Companion Volume) 2018: 639-646 - [i8]Ziqi Liu, Chaochao Chen, Longfei Li, Jun Zhou, Xiaolong Li, Le Song:
GeniePath: Graph Neural Networks with Adaptive Receptive Paths. CoRR abs/1802.00910 (2018) - [i7]Li Wang, Chaochao Chen, Jun Zhou, Xiaolong Li:
Time-sensitive Customer Churn Prediction based on PU Learning. CoRR abs/1802.09788 (2018) - [i6]Chaochao Chen, Ziqi Liu, Peilin Zhao, Longfei Li, Jun Zhou, Xiaolong Li:
Distributed Collaborative Hashing and Its Applications in Ant Financial. CoRR abs/1804.04918 (2018) - [i5]Longfei Li, Peilin Zhao, Jun Zhou, Xiaolong Li:
A Boosting Framework of Factorization Machine. CoRR abs/1804.06027 (2018) - [i4]Biao Xiang, Ziqi Liu, Jun Zhou, Xiaolong Li:
Feature Propagation on Graph: A New Perspective to Graph Representation Learning. CoRR abs/1804.06111 (2018) - [i3]Ya-Lin Zhang, Jun Zhou, Wenhao Zheng, Ji Feng, Longfei Li, Ziqi Liu, Ming Li, Zhiqiang Zhang, Chaochao Chen, Xiaolong Li, Zhi-Hua Zhou:
Distributed Deep Forest and its Application to Automatic Detection of Cash-out Fraud. CoRR abs/1805.04234 (2018) - [i2]Cen Chen, Minghui Qiu, Yinfei Yang, Jun Zhou, Jun Huang, Xiaolong Li, Forrest Sheng Bao:
Review Helpfulness Prediction with Embedding-Gated CNN. CoRR abs/1808.09896 (2018) - 2017
- [c10]Chaochao Chen, Xinxing Yang, Li Wang, Jun Zhou, Xiaolong Li:
Large scale app recommendation in Ant Financial. IEEE BigData 2017: 4733-4735 - [c9]Shaosheng Cao, Xinxing Yang, Jun Zhou, Xiaolong Li, Yuan (Alan) Qi, Kai Xiao:
POSTER: Actively Detecting Implicit Fraudulent Transactions. CCS 2017: 2475-2477 - [c8]Longfei Li, Jun Zhou, Xiaolong Li, Tao Chen:
POSTER: Practical Fraud Transaction Prediction. CCS 2017: 2535-2537 - [c7]Ziqi Liu, Chaochao Chen, Jun Zhou, Xiaolong Li, Feng Xu, Tao Chen, Le Song:
POSTER: Neural Network-based Graph Embedding for Malicious Accounts Detection. CCS 2017: 2543-2545 - [c6]Ya-Lin Zhang, Longfei Li, Jun Zhou, Xiaolong Li, Yujiang Liu, Yuanchao Zhang, Zhi-Hua Zhou:
POSTER: A PU Learning based System for Potential Malicious URL Detection. CCS 2017: 2599-2601 - [c5]Chenghao Liu, Teng Zhang, Peilin Zhao, Jun Zhou, Jianling Sun:
Locally Linear Factorization Machines. IJCAI 2017: 2294-2300 - [c4]Jun Zhou, Xiaolong Li, Peilin Zhao, Chaochao Chen, Longfei Li, Xinxing Yang, Qing Cui, Jin Yu, Xu Chen, Yi Ding, Yuan (Alan) Qi:
KunPeng: Parameter Server based Distributed Learning Systems and Its Applications in Alibaba and Ant Financial. KDD 2017: 1693-1702 - [c3]Shaosheng Cao, Wei Lu, Jun Zhou, Xiaolong Li:
Investigating Stroke-Level Information for Learning Chinese Word Embeddings. ISWC (Posters, Demos & Industry Tracks) 2017 - [c2]Cen Chen, Peilin Zhao, Longfei Li, Jun Zhou, Xiaolong Li, Minghui Qiu:
Locally Connected Deep Learning Framework for Industrial-scale Recommender Systems. WWW (Companion Volume) 2017: 769-770 - [c1]Jun Zhou, Qing Cui, Xiaolong Li, Peilin Zhao, Shenquan Qu, Jun Huang:
PSMART: Parameter Server based Multiple Additive Regression Trees System. WWW (Companion Volume) 2017: 879-880 - [i1]Zhiming Wang, Xiaolong Li, Jun Zhou:
Small-footprint Keyword Spotting Using Deep Neural Network and Connectionist Temporal Classifier. CoRR abs/1709.03665 (2017)
Coauthor Index
[j25] [j24] [j16] [j11] [c150] [i93] [i82] [j8] [j7] [c88] [c87] [c79] [j6] [j5] [c71] [c59] [c57] [i53] [i50] [i45] [j3] [c50] [c46] [c44] [i44] [i43] [i42] [i41] [i39] [i31] [i30] [i29] [i24] [i23] [i22] [i20] [i16] [i14] [j1] [c33] [c32] [c26] [c25] [i12] [i10] [i9] [c20] [c17] [c16] [c14] [c12] [i8] [i7] [i6] [i3] [c10] [c7] [c4]
[j27] [c210] [c208] [c207] [c201] [c200] [c199] [c193] [c189] [c184] [c183] [c182] [c179] [c176] [c172] [c171] [c167] [i117] [j19] [j18] [j11] [c164] [c161] [c156] [c151] [c150] [c147] [c146] [c144] [c143] [c138] [c136] [c129] [c124] [c123] [c122] [c121] [c116] [c115] [i93] [i88] [i79] [i77] [i71] [j9] [j8] [c109] [c108] [c107] [c105] [c104] [c102] [c99] [c84] [c83] [c79] [i54] [j6] [c63] [c61] [c59] [c58] [c51] [i53] [i50] [c42] [c37] [c36] [i33] [i18] [i15] [j1] [c33] [i9] [c14] [c11] [i8] [i6] [i5] [i3] [c8] [c6] [c4] [c2]
[c209] [c197] [c195] [c180] [c165] [i119] [i118] [i109] [i108] [i107] [i104] [i97] [j17] [j10] [c126] [c118] [c112] [i89] [i69] [i67] [c103] [c98] [c90] [c88] [c87] [i65] [i55] [j6] [c72] [c68] [c56] [i48] [i47] [i45] [j4] [c40] [c39] [i42] [i40] [i39] [i38] [i35] [i34] [i32] [i29] [i22] [i21] [j1] [c33] [c31] [c30] [c29] [c25] [c23] [i9] [c20] [c17] [c14] [i8] [i6] [i4] [i3] [c7]
Yuan Qi 0001
aka: Yuan (Alan) Qi
aka: Yuan (Alan) Qi
[j22] [c205] [c202] [c190] [c188] [c178] [c177] [c170] [c169] [i120] [i116] [i114] [i113] [i110] [c160] [c159] [c158] [c155] [c145] [c141] [c133] [c131] [c128] [c114] [i91] [i78] [i74] [i72] [i66] [c100] [c96] [c91] [c86] [c82] [c78] [i59] [c64] [c60] [c52] [i51] [c50] [c49] [c47] [c38] [i36] [c27] [c26] [c22] [i12] [i11] [i10]
[j21] [j20] [c209] [c204] [c198] [c197] [c196] [c195] [c181] [c180] [c175] [c174] [c173] [c168] [c166] [c165] [i121] [i119] [i118] [i115] [i109] [i108] [i107] [i104] [i101] [i100] [i97] [i94] [j10] [c163] [c162] [c154] [c153] [c149] [c148] [c142] [c140] [c134] [c132] [c130] [c127] [c126] [c118] [c117] [c113] [i92] [i90] [i89] [i86] [i85] [i84] [i76] [i70] [i69] [i68] [i67] [j8] [c111] [c110] [c101] [c90] [c89] [c87] [c85] [c81] [c80] [c75] [c74] [c73] [i64] [i63] [i62] [i60] [i58] [c72] [c70] [c69] [c68] [c67] [c66] [c62] [c56] [c54] [c53] [i49] [i47] [i46] [i45] [j4] [c48] [c45] [c41] [c40] [c39] [i40] [i35] [i34] [i26] [i21] [i19] [j1] [c34] [c31] [c29] [c18] [c16] [i3]
Leon Wenliang Zhong
aka: Wenliang Zhong
aka: Wenliang Zhong
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