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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.dagstuhl.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) - [c206]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 - [c205]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 - [c204]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 - [c203]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 - [c202]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 - [c201]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 - [c200]Fuwei Zhang, Zhao Zhang, Fuzhen Zhuang, Zhiqiang Zhang, Jun Zhou, Deqing Wang:
Multi-view Temporal Knowledge Graph Reasoning. CIKM 2024: 4263-4267 - [c199]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 - [c198]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 - [c197]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 - [c196]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 - [c195]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 - [c194]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 - [c193]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 - [c192]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 - [c191]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 - [c190]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 - [c189]Kaituo Feng, Changsheng Li, Xiaolu Zhang, Jun Zhou, Ye Yuan, Guoren Wang:
Keypoint-based Progressive Chain-of-Thought Distillation for LLMs. ICML 2024 - [c188]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 - [c187]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 - [c186]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 - [c185]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 - [c184]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 - [c183]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 - [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 - [i118]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) - [i117]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) - [i116]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) - [i115]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) - [i114]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) - [i113]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) - [i112]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) - [i111]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) - [i110]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) - [i109]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) - [i108]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) - [i107]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) - [i106]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) - [i105]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) - [i104]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) - [i103]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) - [i102]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) - [i101]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) - [i100]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) - [i99]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) - [i98]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) - [i97]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) - [i96]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) - [i95]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) - [i94]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) - 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:
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