Jun Zhou

ORCID

Publication Activity (10 Years)

Years Active: 2017-2024
Publications (10 Years): 252

Top Venues

Publications

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)
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 (2024)
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 (2024)
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)
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)
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)
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)
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) (2024)
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 (2024)
Bin Han, Ya-Lin Zhang, Lu Yu, Biying Chen, Longfei Li, Jun Zhou
Modeling Treatment Effect with Cross-Domain Data. PAKDD (1) (2024)
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 (2024)
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 (2024)
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 (2024)
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)
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)
Kaituo Feng, Changsheng Li, Xiaolu Zhang, Jun Zhou, Ye Yuan, Guoren Wang
Keypoint-based Progressive Chain-of-Thought Distillation for LLMs. CoRR (2024)
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)
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)
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 (2024)
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)
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)
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)
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) (2024)
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 (2024)
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)
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 (2024)
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 (2024)
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)
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)
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) (2024)
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)
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)
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 (2024)
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)
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)
Changxin Tian, Binbin Hu, Wayne Xin Zhao, Zhiqiang Zhang, Jun Zhou
Periodicity May Be Emanative: Hierarchical Contrastive Learning for Sequential Recommendation. CIKM (2023)
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)
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)
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)
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)
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 (2023)
Daohong Jian, Yang Bao, Jun Zhou, Hua Wu
A Practical Online Allocation Framework at Industry-scale in Constrained Recommendation. SIGIR (2023)
Zuoli Tang, Lin Wang, Lixin Zou, Xiaolu Zhang, Jun Zhou, Chenliang Li
Towards Multi-Interest Pre-training with Sparse Capsule Network. SIGIR (2023)
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)
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 (2023)
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)
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)
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)
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) (2023)
Kaituo Feng, Changsheng Li, Xiaolu Zhang, Jun Zhou
Towards Open Temporal Graph Neural Networks. ICLR (2023)
Lu Yu, Meng Li, Ya-Lin Zhang, Longfei Li, Jun Zhou
FINRule: Feature Interactive Neural Rule Learning. CIKM (2023)
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)
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)
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)
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)
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)
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 (2023)
Yi-Xuan Sun, Ya-Lin Zhang, Wei Wang, Longfei Li, Jun Zhou
Treatment Effect Estimation across Domains. CIKM (2023)
Jun Zhou, Yang Bao, Daohong Jian, Hua Wu
PDAS: A Practical Distributed ADMM System for Large-Scale Linear Programming Problems at Alipay. KDD (2023)
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 (2023)
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 (2023)
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 (2023)
Shaowei Wei, Zhengwei Wu, Zhiqiang Zhang, Jun Zhou
Boosting Adaptive Graph Augmented MLPs via Customized Knowledge Distillation. ECML/PKDD (3) (2023)
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) (2023)
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)
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)
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) (2023)
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 (2023)
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)
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) (2023)
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) (2023)
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 (2023)
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) (2023)
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)
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) (2023)
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 (2023)
Jun Zhou, Chilin Fu, Xiaolu Zhang
Multi-Source Domain Adaptation via Latent Domain Reconstruction. WWW (Companion Volume) (2023)
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 (2023)
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)
Chaochao Chen, Xiaohua Feng, Jun Zhou, Jianwei Yin, Xiaolin Zheng
Federated Large Language Model: A Position Paper. CoRR (2023)
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)
Qian Zhao, Zhengwei Wu, Zhiqiang Zhang, Jun Zhou
Long-tail Augmented Graph Contrastive Learning for Recommendation. CoRR (2023)
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)
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)
Kaituo Feng, Changsheng Li, Xiaolu Zhang, Jun Zhou
Towards Open Temporal Graph Neural Networks. CoRR (2023)
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)
Yonghui Yang, Zhengwei Wu, Le Wu, Kun Zhang, Richang Hong, Zhiqiang Zhang, Jun Zhou, Meng Wang
Generative-Contrastive Graph Learning for Recommendation. SIGIR (2023)
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 (2023)
Caizhi Tang, Qing Cui, Longfei Li, Jun Zhou
GINT: A Generative Interpretability method via perturbation in the latent space. Expert Syst. Appl. 232 (2023)
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)
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 (2023)
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 (2023)
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)
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 (2023)
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) (2023)
Qian Zhao, Zhengwei Wu, Zhiqiang Zhang, Jun Zhou
Long-Tail Augmented Graph Contrastive Learning for Recommendation. ECML/PKDD (4) (2023)
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)
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)
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)
Shih-Han Chan, Yinpeng Dong, Jun Zhu, Xiaolu Zhang, Jun Zhou
BadDet: Backdoor Attacks on Object Detection. ECCV Workshops (1) (2022)

Jun Zhou.css-eqlu8i{font-size:small;padding-left:4px;}

Publication Activity (10 Years)

Top Topics

Top Venues

Jun Zhou