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ORCIDXiuqiang He 0001
XiuQiang He 0001
Person information
- affiliation: Tencent, FiT, Shenzhen, China
- affiliation (former): Huawei, Noah's Ark Lab, Shenzhen, China
- affiliation (PhD): Hong Kong University of Science and Technology (HKUST), Department of Computer Science and Engineering, Hong Kong
- affiliation (former): Xi'an Jiaotong University, School of Electronics and Information Engineering, China
Other persons with the same name
- Xiuqiang He 0002
![[0000-0002-3755-7553]](https://dblp.org/img/orcid-mark.12x12.png "0000-0002-3755-7553")
— ETH Zurich, Automatic Control Laboratory; Zürich, Switzerland (and 1 more)
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2020 – today
- 2024
[c93]Zexu Sun, Dugang Liu, Xing Tang, Yunpeng Weng, Xiuqiang He:
Towards Effective and Efficient Multi-valued Treatment Uplift Modeling in Online Marketing. DASFAA (7) 2024: 121-138- [c92]Shiwei Li, Wenchao Xu, Haozhao Wang, Xing Tang, Yining Qi, Shijie Xu, Weihong Luo, Yuhua Li, Xiuqiang He, Ruixuan Li:
FedBAT: Communication-Efficient Federated Learning via Learnable Binarization. ICML 2024 - [c91]Bowei He, Yunpeng Weng, Xing Tang, Ziqiang Cui, Zexu Sun, Liang Chen, Xiuqiang He, Chen Ma:
Rankability-enhanced Revenue Uplift Modeling Framework for Online Marketing. KDD 2024: 5093-5104 - [c90]Ziqiang Cui, Xing Tang, Yang Qiao, Bowei He, Liang Chen, Xiuqiang He, Chen Ma:
Treatment-Aware Hyperbolic Representation Learning for Causal Effect Estimation with Social Networks. SDM 2024: 289-297 - [c89]Dugang Liu, Shenxian Xian, Yuhao Wu, Chaohua Yang, Xing Tang, Xiuqiang He, Zhong Ming:
AutoDCS: Automated Decision Chain Selection in Deep Recommender Systems. SIGIR 2024: 956-965 - [c88]Dugang Liu, Chaohua Yang, Xing Tang, Yejing Wang, Fuyuan Lyu, Weihong Luo, Xiuqiang He, Zhong Ming, Xiangyu Zhao:
MultiFS: Automated Multi-Scenario Feature Selection in Deep Recommender Systems. WSDM 2024: 434-442 - [i67]Yunpeng Weng, Xing Tang, Liang Chen, Dugang Liu, Xiuqiang He:
Expected Transaction Value Optimization for Precise Marketing in FinTech Platforms. CoRR abs/2401.01525 (2024) - [i66]Yuheng Cheng, Ceyao Zhang, Zhengwen Zhang, Xiangrui Meng, Sirui Hong, Wenhao Li, Zihao Wang, Zekai Wang, Feng Yin, Junhua Zhao, Xiuqiang He:
Exploring Large Language Model based Intelligent Agents: Definitions, Methods, and Prospects. CoRR abs/2401.03428 (2024) - [i65]Ziqiang Cui, Xing Tang, Yang Qiao, Bowei He, Liang Chen, Xiuqiang He, Chen Ma:
Treatment-Aware Hyperbolic Representation Learning for Causal Effect Estimation with Social Networks. CoRR abs/2401.06557 (2024) - [i64]Xing Tang, Yang Qiao, Fuyuan Lyu, Dugang Liu, Xiuqiang He:
Touch the Core: Exploring Task Dependence Among Hybrid Targets for Recommendation. CoRR abs/2403.17442 (2024) - [i63]Bowei He, Yunpeng Weng, Xing Tang, Ziqiang Cui, Zexu Sun, Liang Chen, Xiuqiang He, Chen Ma:
Rankability-enhanced Revenue Uplift Modeling Framework for Online Marketing. CoRR abs/2405.15301 (2024) - [i62]Dugang Liu, Xing Tang, Yang Qiao, Miao Liu, Zexu Sun, Xiuqiang He, Zhong Ming:
Benchmarking for Deep Uplift Modeling in Online Marketing. CoRR abs/2406.00335 (2024) - [i61]Shiwei Li, Wenchao Xu, Haozhao Wang, Xing Tang, Yining Qi, Shijie Xu, Weihong Luo, Yuhua Li, Xiuqiang He, Ruixuan Li:
FedBAT: Communication-Efficient Federated Learning via Learnable Binarization. CoRR abs/2408.03215 (2024) - [i60]Shiwei Li, Yingyi Cheng, Haozhao Wang, Xing Tang, Shijie Xu, Weihong Luo, Yuhua Li, Dugang Liu, Xiuqiang He, Ruixuan Li:
Masked Random Noise for Communication Efficient Federaetd Learning. CoRR abs/2408.03220 (2024) - [i59]Yunpeng Weng, Xing Tang, Zhenhao Xu, Fuyuan Lyu, Dugang Liu, Zexu Sun, Xiuqiang He:
OptDist: Learning Optimal Distribution for Customer Lifetime Value Prediction. CoRR abs/2408.08585 (2024) - [i58]Zexu Sun, Hao Yang, Dugang Liu, Yunpeng Weng, Xing Tang, Xiuqiang He:
End-to-End Cost-Effective Incentive Recommendation under Budget Constraint with Uplift Modeling. CoRR abs/2408.11623 (2024) - 2023
- [j22]Chenxu Zhu, Bo Chen, Weinan Zhang, Jincai Lai, Ruiming Tang, Xiuqiang He, Zhenguo Li, Yong Yu:
AIM: Automatic Interaction Machine for Click-Through Rate Prediction. IEEE Trans. Knowl. Data Eng. 35(4): 3389-3403 (2023) - [j21]Haokun Chen, Chenxu Zhu, Ruiming Tang, Weinan Zhang, Xiuqiang He, Yong Yu:
Large-Scale Interactive Recommendation With Tree-Structured Reinforcement Learning. IEEE Trans. Knowl. Data Eng. 35(4): 4018-4032 (2023) - [j20]Dugang Liu, Pengxiang Cheng, Zinan Lin, Jinwei Luo, Zhenhua Dong, Xiuqiang He, Weike Pan, Zhong Ming:
KDCRec: Knowledge Distillation for Counterfactual Recommendation via Uniform Data. IEEE Trans. Knowl. Data Eng. 35(8): 8143-8156 (2023) - [j19]Jiarui Qin, Weinan Zhang, Rong Su, Zhirong Liu, Weiwen Liu, Guangpeng Zhao, Hao Li, Ruiming Tang, Xiuqiang He, Yong Yu:
Learning to Retrieve User Behaviors for Click-through Rate Estimation. ACM Trans. Inf. Syst. 41(4): 98:1-98:31 (2023) - [j18]Dugang Liu, Pengxiang Cheng, Zinan Lin, Xiaolian Zhang, Zhenhua Dong, Rui Zhang, Xiuqiang He, Weike Pan, Zhong Ming:
Bounding System-Induced Biases in Recommender Systems with a Randomized Dataset. ACM Trans. Inf. Syst. 41(4): 108:1-108:26 (2023) - [j17]Mengyue Yang, Guohao Cai, Furui Liu, Jiarui Jin, Zhenhua Dong, Xiuqiang He, Jianye Hao, Weiqi Shao, Jun Wang, Xu Chen:
Debiased Recommendation with User Feature Balancing. ACM Trans. Inf. Syst. 41(4): 114:1-114:25 (2023) - [j16]Dugang Liu, Pengxiang Cheng, Hong Zhu, Zhenhua Dong, Xiuqiang He, Weike Pan, Zhong Ming:
Debiased Representation Learning in Recommendation via Information Bottleneck. Trans. Recomm. Syst. 1(1): 1-27 (2023) - [c87]Dugang Liu, Yang Qiao, Xing Tang, Liang Chen, Xiuqiang He, Weike Pan, Zhong Ming:
Self-Sampling Training and Evaluation for the Accuracy-Bias Tradeoff in Recommendation. DASFAA (4) 2023: 580-592 - [c86]Dugang Liu, Xing Tang, Han Gao, Fuyuan Lyu, Xiuqiang He:
Explicit Feature Interaction-aware Uplift Network for Online Marketing. KDD 2023: 4507-4515 - [c85]Dugang Liu, Yang Qiao, Xing Tang, Liang Chen, Xiuqiang He, Zhong Ming:
Prior-Guided Accuracy-Bias Tradeoff Learning for CTR Prediction in Multimedia Recommendation. ACM Multimedia 2023: 995-1003 - [c84]Fuyuan Lyu, Xing Tang, Dugang Liu, Chen Ma, Weihong Luo, Liang Chen, Xiuqiang He, Xue (Steve) Liu:
Towards Hybrid-grained Feature Interaction Selection for Deep Sparse Network. NeurIPS 2023 - [c83]Xing Tang, Yang Qiao, Yuwen Fu, Fuyuan Lyu, Dugang Liu, Xiuqiang He:
OptMSM: Optimizing Multi-Scenario Modeling for Click-Through Rate Prediction. ECML/PKDD (6) 2023: 567-584 - [c82]Yunpeng Weng, Xing Tang, Liang Chen, Xiuqiang He:
Curriculum Modeling the Dependence among Targets with Multi-task Learning for Financial Marketing. SIGIR 2023: 1914-1918 - [c81]Dugang Liu, Pengxiang Cheng, Hong Zhu, Xing Tang, Yanyu Chen, Xiaoting Wang, Weike Pan, Zhong Ming, Xiuqiang He:
DIWIFT: Discovering Instance-wise Influential Features for Tabular Data. WWW 2023: 1673-1682 - [c80]Fuyuan Lyu, Xing Tang, Dugang Liu, Liang Chen, Xiuqiang He, Xue Liu:
Optimizing Feature Set for Click-Through Rate Prediction. WWW 2023: 3386-3395 - [i57]Fuyuan Lyu, Xing Tang, Dugang Liu, Liang Chen, Xiuqiang He, Xue Liu:
Optimizing Feature Set for Click-Through Rate Prediction. CoRR abs/2301.10909 (2023) - [i56]Fuyuan Lyu, Xing Tang, Dugang Liu, Haolun Wu, Chen Ma, Xiuqiang He, Xue Liu:
Feature Representation Learning for Click-through Rate Prediction: A Review and New Perspectives. CoRR abs/2302.02241 (2023) - [i55]Dugang Liu, Yang Qiao, Xing Tang, Liang Chen, Xiuqiang He, Weike Pan, Zhong Ming:
Self-Sampling Training and Evaluation for the Accuracy-Bias Tradeoff in Recommendation. CoRR abs/2302.03419 (2023) - [i54]Dugang Liu, Pengxiang Cheng, Zinan Lin, Xiaolian Zhang, Zhenhua Dong, Rui Zhang, Xiuqiang He, Weike Pan, Zhong Ming:
Bounding System-Induced Biases in Recommender Systems with A Randomized Dataset. CoRR abs/2303.11574 (2023) - [i53]Yunpeng Weng, Xing Tang, Liang Chen, Xiuqiang He:
Curriculum Modeling the Dependence among Targets with Multi-task Learning for Financial Marketing. CoRR abs/2305.01514 (2023) - [i52]Dugang Liu, Xing Tang, Han Gao, Fuyuan Lyu, Xiuqiang He:
Explicit Feature Interaction-aware Uplift Network for Online Marketing. CoRR abs/2306.00315 (2023) - [i51]Xing Tang, Yang Qiao, Yuwen Fu, Fuyuan Lyu, Dugang Liu, Xiuqiang He:
OptMSM: Optimizing Multi-Scenario Modeling for Click-Through Rate Prediction. CoRR abs/2306.13382 (2023) - [i50]Fuyuan Lyu, Xing Tang, Dugang Liu, Chen Ma, Weihong Luo, Liang Chen, Xiuqiang He, Xue Liu:
Towards Hybrid-grained Feature Interaction Selection for Deep Sparse Network. CoRR abs/2310.15342 (2023) - 2022
- [j15]Xiangli Yang, Qing Liu, Rong Su, Ruiming Tang, Zhirong Liu, Xiuqiang He, Jianxi Yang:
Click-through rate prediction using transfer learning with fine-tuned parameters. Inf. Sci. 612: 188-200 (2022) - [j14]Guibing Guo, Huan Zhou, Bowei Chen, Zhirong Liu, Xiao Xu, Xu Chen, Zhenhua Dong, Xiuqiang He:
IPGAN: Generating Informative Item Pairs by Adversarial Sampling. IEEE Trans. Neural Networks Learn. Syst. 33(2): 694-706 (2022) - [j13]Xinyi Dai, Yunjia Xi, Weinan Zhang, Qing Liu, Ruiming Tang, Xiuqiang He, Jiawei Hou, Jun Wang, Yong Yu:
Beyond Relevance Ranking: A General Graph Matching Framework for Utility-Oriented Learning to Rank. ACM Trans. Inf. Syst. 40(2): 25:1-25:29 (2022) - [c79]Runpeng Yu, Hong Zhu, Kaican Li, Lanqing Hong, Rui Zhang, Nanyang Ye, Shao-Lun Huang, Xiuqiang He:
Regularization Penalty Optimization for Addressing Data Quality Variance in OoD Algorithms. AAAI 2022: 8945-8953 - [c78]Wenwen Pan, Haonan Shi, Zhou Zhao, Jieming Zhu, Xiuqiang He, Zhigeng Pan, Lianli Gao, Jun Yu, Fei Wu, Qi Tian:
Wnet: Audio-Guided Video Object Segmentation via Wavelet-Based Cross- Modal Denoising Networks. CVPR 2022: 1310-1321 - [c77]Wei Guo, Can Zhang, Zhicheng He, Jiarui Qin, Huifeng Guo, Bo Chen, Ruiming Tang, Xiuqiang He, Rui Zhang:
MISS: Multi-Interest Self-Supervised Learning Framework for Click-Through Rate Prediction. ICDE 2022: 727-740 - [c76]Fuyuan Lyu, Xing Tang, Huifeng Guo, Ruiming Tang, Xiuqiang He, Rui Zhang, Xue Liu:
Memorize, Factorize, or be Naive: Learning Optimal Feature Interaction Methods for CTR Prediction. ICDE 2022: 1450-1462 - [c75]Guohao Cai, Jieming Zhu, Quanyu Dai, Zhenhua Dong, Xiuqiang He, Ruiming Tang, Rui Zhang:
ReLoop: A Self-Correction Continual Learning Loop for Recommender Systems. SIGIR 2022: 2692-2697 - [c74]Xiangsheng Li, Jiaxin Mao, Weizhi Ma, Zhijing Wu, Yiqun Liu, Min Zhang, Shaoping Ma, Zhaowei Wang, Xiuqiang He:
A Cooperative Neural Information Retrieval Pipeline with Knowledge Enhanced Automatic Query Reformulation. WSDM 2022: 553-561 - [c73]Ting Long, Jiarui Qin, Jian Shen, Weinan Zhang, Wei Xia, Ruiming Tang, Xiuqiang He, Yong Yu:
Improving Knowledge Tracing with Collaborative Information. WSDM 2022: 599-607 - [c72]Lu Wang, Ruiming Tang, Xiaofeng He, Xiuqiang He:
Hierarchical Imitation Learning via Subgoal Representation Learning for Dynamic Treatment Recommendation. WSDM 2022: 1081-1089 - [c71]Yi Li, Jieming Zhu, Weiwen Liu, Liangcai Su, Guohao Cai, Qi Zhang, Ruiming Tang, Xi Xiao, Xiuqiang He:
PEAR: Personalized Re-ranking with Contextualized Transformer for Recommendation. WWW (Companion Volume) 2022: 62-66 - [c70]Dong Yao, Zhou Zhao, Shengyu Zhang, Jieming Zhu, Yudong Zhu, Rui Zhang, Xiuqiang He:
Contrastive Learning with Positive-Negative Frame Mask for Music Representation. WWW 2022: 2906-2915 - [i49]Mengyue Yang, Guohao Cai, Furui Liu, Zhenhua Dong, Xiuqiang He, Jianye Hao, Jun Wang, Xu Chen:
Debiased Recommendation with User Feature Balancing. CoRR abs/2201.06056 (2022) - [i48]Dong Yao, Zhou Zhao, Shengyu Zhang, Jieming Zhu, Yudong Zhu, Rui Zhang, Xiuqiang He:
Contrastive Learning with Positive-Negative Frame Mask for Music Representation. CoRR abs/2203.09129 (2022) - [i47]Yi Li, Jieming Zhu, Weiwen Liu, Liangcai Su, Guohao Cai, Qi Zhang, Ruiming Tang, Xi Xiao, Xiuqiang He:
PEAR: Personalized Re-ranking with Contextualized Transformer for Recommendation. CoRR abs/2203.12267 (2022) - [i46]Guohao Cai, Jieming Zhu, Quanyu Dai, Zhenhua Dong, Xiuqiang He, Ruiming Tang, Rui Zhang:
ReLoop: A Self-Correction Continual Learning Loop for Recommender Systems. CoRR abs/2204.11165 (2022) - [i45]Runpeng Yu, Hong Zhu, Kaican Li, Lanqing Hong, Rui Zhang, Nanyang Ye, Shao-Lun Huang, Xiuqiang He:
Regularization Penalty Optimization for Addressing Data Quality Variance in OoD Algorithms. CoRR abs/2206.05749 (2022) - [i44]Jianghao Lin, Weiwen Liu, Xinyi Dai, Weinan Zhang, Shuai Li, Ruiming Tang, Xiuqiang He, Jianye Hao, Yong Yu:
A Graph-Enhanced Click Model for Web Search. CoRR abs/2206.08621 (2022) - [i43]Pengxiang Cheng, Hong Zhu, Xing Tang, Dugang Liu, Yanyu Chen, Xiaoting Wang, Weike Pan, Zhong Ming, Xiuqiang He:
DIWIFT: Discovering Instance-wise Influential Features for Tabular Data. CoRR abs/2207.02773 (2022) - 2021
- [j12]Handong Ma, Jiawei Hou, Chenxu Zhu, Weinan Zhang, Ruiming Tang, Jincai Lai, Jieming Zhu, Xiuqiang He, Yong Yu:
QA4PRF: A Question Answering Based Framework for Pseudo Relevance Feedback. IEEE Access 9: 139303-139314 (2021) - [j11]Weike Jin, Zhou Zhao, Xiaochun Cao, Jieming Zhu, Xiuqiang He, Yueting Zhuang:
Adaptive Spatio-Temporal Graph Enhanced Vision-Language Representation for Video QA. IEEE Trans. Image Process. 30: 5477-5489 (2021) - [j10]Yi Ouyang, Bin Guo, Xing Tang, Xiuqiang He, Jian Xiong, Zhiwen Yu:
Mobile App Cross-Domain Recommendation with Multi-Graph Neural Network. ACM Trans. Knowl. Discov. Data 15(4): 55:1-55:21 (2021) - [c69]Chong Chen, Weizhi Ma, Min Zhang, Zhaowei Wang, Xiuqiang He, Chenyang Wang, Yiqun Liu, Shaoping Ma:
Graph Heterogeneous Multi-Relational Recommendation. AAAI 2021: 3958-3966 - [c68]Dong Yao, Shengyu Zhang, Zhou Zhao, Wenyan Fan, Jieming Zhu, Xiuqiang He, Fei Wu:
Modeling High-order Interactions across Multi-interests for Micro-video Reommendation (Student Abstract). AAAI 2021: 15945-15946 - [c67]Kelong Mao, Jieming Zhu, Jinpeng Wang, Quanyu Dai, Zhenhua Dong, Xi Xiao, Xiuqiang He:
SimpleX: A Simple and Strong Baseline for Collaborative Filtering. CIKM 2021: 1243-1252 - [c66]Kelong Mao, Jieming Zhu, Xi Xiao, Biao Lu, Zhaowei Wang, Xiuqiang He:
UltraGCN: Ultra Simplification of Graph Convolutional Networks for Recommendation. CIKM 2021: 1253-1262 - [c65]Mengyue Yang, Quanyu Dai, Zhenhua Dong, Xu Chen, Xiuqiang He, Jun Wang:
Top-N Recommendation with Counterfactual User Preference Simulation. CIKM 2021: 2342-2351 - [c64]Jieming Zhu, Jinyang Liu, Shuai Yang, Qi Zhang, Xiuqiang He:
Open Benchmarking for Click-Through Rate Prediction. CIKM 2021: 2759-2769 - [c63]Bo Chen, Yichao Wang, Zhirong Liu, Ruiming Tang, Wei Guo, Hongkun Zheng, Weiwei Yao, Muyu Zhang, Xiuqiang He:
Enhancing Explicit and Implicit Feature Interactions via Information Sharing for Parallel Deep CTR Models. CIKM 2021: 3757-3766 - [c62]Qi Zhang, Jingjie Li, Qinglin Jia, Chuyuan Wang, Jieming Zhu, Zhaowei Wang, Xiuqiang He:
UNBERT: User-News Matching BERT for News Recommendation. IJCAI 2021: 3356-3362 - [c61]Weinan Zhang, Jiarui Qin, Wei Guo, Ruiming Tang, Xiuqiang He:
Deep Learning for Click-Through Rate Estimation. IJCAI 2021: 4695-4703 - [c60]Qiming Zheng, Quan Chen, Kaihao Bai, Huifeng Guo, Yong Gao, Xiuqiang He, Minyi Guo:
BiPS: Hotness-aware Bi-tier Parameter Synchronization for Recommendation Models. IPDPS 2021: 609-618 - [c59]Wei Guo, Rong Su, Renhao Tan, Huifeng Guo, Yingxue Zhang, Zhirong Liu, Ruiming Tang, Xiuqiang He:
Dual Graph enhanced Embedding Neural Network for CTR Prediction. KDD 2021: 496-504 - [c58]Jiarui Qin, Weinan Zhang, Rong Su, Zhirong Liu, Weiwen Liu, Ruiming Tang, Xiuqiang He, Yong Yu:
Retrieval & Interaction Machine for Tabular Data Prediction. KDD 2021: 1379-1389 - [c57]Huifeng Guo, Bo Chen, Ruiming Tang, Weinan Zhang, Zhenguo Li, Xiuqiang He:
An Embedding Learning Framework for Numerical Features in CTR Prediction. KDD 2021: 2910-2918 - [c56]Guohao Cai, Xiaoguang Li, Quanyu Dai, Gang Wang, Zhenhua Dong, Chaoliang Zhang, Xiuqiang He, Lifeng Shang:
Dual Sequence Transformer for Query-based Interactive Recommendation. MDM 2021: 139-144 - [c55]Jiahao Xun, Shengyu Zhang, Zhou Zhao, Jieming Zhu, Qi Zhang, Jingjie Li, Xiuqiang He, Xiaofei He, Tat-Seng Chua, Fei Wu:
Why Do We Click: Visual Impression-aware News Recommendation. ACM Multimedia 2021: 3881-3890 - [c54]Dugang Liu, Pengxiang Cheng, Hong Zhu, Zhenhua Dong, Xiuqiang He, Weike Pan, Zhong Ming:
Mitigating Confounding Bias in Recommendation via Information Bottleneck. RecSys 2021: 351-360 - [c53]Weike Jin, Zhou Zhao, Pengcheng Zhang, Jieming Zhu, Xiuqiang He, Yueting Zhuang:
Hierarchical Cross-Modal Graph Consistency Learning for Video-Text Retrieval. SIGIR 2021: 1114-1124 - [c52]Jianghao Lin, Weiwen Liu, Xinyi Dai, Weinan Zhang, Shuai Li, Ruiming Tang, Xiuqiang He, Jianye Hao, Yong Yu:
A Graph-Enhanced Click Model for Web Search. SIGIR 2021: 1259-1268 - [c51]Huifeng Guo, Wei Guo, Yong Gao, Ruiming Tang, Xiuqiang He, Wenzhi Liu:
ScaleFreeCTR: MixCache-based Distributed Training System for CTR Models with Huge Embedding Table. SIGIR 2021: 1269-1278 - [c50]Qi Zhang, Qinglin Jia, Chuyuan Wang, Jingjie Li, Zhaowei Wang, Xiuqiang He:
AMM: Attentive Multi-field Matching for News Recommendation. SIGIR 2021: 1588-1592 - [c49]Jinpeng Wang, Jieming Zhu, Xiuqiang He:
Cross-Batch Negative Sampling for Training Two-Tower Recommenders. SIGIR 2021: 1632-1636 - [c48]Qinglin Jia, Jingjie Li, Qi Zhang, Xiuqiang He, Jieming Zhu:
RMBERT: News Recommendation via Recurrent Reasoning Memory Network over BERT. SIGIR 2021: 1773-1777 - [c47]Xiangsheng Li, Jiaxin Mao, Weizhi Ma, Yiqun Liu, Min Zhang, Shaoping Ma, Zhaowei Wang, Xiuqiang He:
Topic-enhanced knowledge-aware retrieval model for diverse relevance estimation. WWW 2021: 756-767 - [c46]Xinyi Dai, Jianghao Lin, Weinan Zhang, Shuai Li, Weiwen Liu, Ruiming Tang, Xiuqiang He, Jianye Hao, Jun Wang, Yong Yu:
An Adversarial Imitation Click Model for Information Retrieval. WWW 2021: 1809-1820 - [i42]Dong Yao, Shengyu Zhang, Zhou Zhao, Wenyan Fan, Jieming Zhu, Xiuqiang He, Fei Wu:
Modeling High-order Interactions across Multi-interests for Micro-video Reommendation. CoRR abs/2104.00305 (2021) - [i41]Xinyi Dai, Jianghao Lin, Weinan Zhang, Shuai Li, Weiwen Liu, Ruiming Tang, Xiuqiang He, Jianye Hao, Jun Wang, Yong Yu:
An Adversarial Imitation Click Model for Information Retrieval. CoRR abs/2104.06077 (2021) - [i40]Huifeng Guo, Wei Guo, Yong Gao, Ruiming Tang, Xiuqiang He, Wenzhi Liu:
ScaleFreeCTR: MixCache-based Distributed Training System for CTR Models with Huge Embedding Table. CoRR abs/2104.08542 (2021) - [i39]Weinan Zhang, Jiarui Qin, Wei Guo, Ruiming Tang, Xiuqiang He:
Deep Learning for Click-Through Rate Estimation. CoRR abs/2104.10584 (2021) - [i38]Wei Guo, Rong Su, Renhao Tan, Huifeng Guo, Yingxue Zhang, Zhirong Liu, Ruiming Tang, Xiuqiang He:
Dual Graph enhanced Embedding Neural Network for CTR Prediction. CoRR abs/2106.00314 (2021) - [i37]Xiangli Yang, Qing Liu, Rong Su, Ruiming Tang, Zhirong Liu, Xiuqiang He:
AutoFT: Automatic Fine-Tune for Parameters Transfer Learning in Click-Through Rate Prediction. CoRR abs/2106.04873 (2021) - [i36]Fuyuan Lyu, Xing Tang, Huifeng Guo, Ruiming Tang, Xiuqiang He, Rui Zhang, Xue Liu:
Memorize, Factorize, or be Naïve: Learning Optimal Feature Interaction Methods for CTR Prediction. CoRR abs/2108.01265 (2021) - [i35]Jiarui Qin, Weinan Zhang, Rong Su, Zhirong Liu, Weiwen Liu, Ruiming Tang, Xiuqiang He, Yong Yu:
Retrieval & Interaction Machine for Tabular Data Prediction. CoRR abs/2108.05252 (2021) - [i34]Lin Bo, Liang Pang, Gang Wang, Jun Xu, XiuQiang He, Ji-Rong Wen:
Modeling Relevance Ranking under the Pre-training and Fine-tuning Paradigm. CoRR abs/2108.05652 (2021) - [i33]Mengyue Yang, Quanyu Dai, Zhenhua Dong, Xu Chen, Xiuqiang He, Jun Wang:
Top-N Recommendation with Counterfactual User Preference Simulation. CoRR abs/2109.02444 (2021) - [i32]Kelong Mao, Jieming Zhu, Jinpeng Wang, Quanyu Dai, Zhenhua Dong, Xi Xiao, Xiuqiang He:
SimpleX: A Simple and Strong Baseline for Collaborative Filtering. CoRR abs/2109.12613 (2021) - [i31]Jiahao Xun, Shengyu Zhang, Zhou Zhao, Jieming Zhu, Qi Zhang, Jingjie Li, Xiuqiang He, Xiaofei He, Tat-Seng Chua, Fei Wu:
Why Do We Click: Visual Impression-aware News Recommendation. CoRR abs/2109.12651 (2021) - [i30]Yunjia Xi, Weiwen Liu, Xinyi Dai, Ruiming Tang, Weinan Zhang, Qing Liu, Xiuqiang He, Yong Yu:
Context-aware Reranking with Utility Maximization for Recommendation. CoRR abs/2110.09059 (2021) - [i29]Yong Gao, Huifeng Guo, Dandan Lin, Yingxue Zhang, Ruiming Tang, Xiuqiang He:
Content Filtering Enriched GNN Framework for News Recommendation. CoRR abs/2110.12681 (2021) - [i28]Kelong Mao, Jieming Zhu, Xi Xiao, Biao Lu, Zhaowei Wang, Xiuqiang He:
UltraGCN: Ultra Simplification of Graph Convolutional Networks for Recommendation. CoRR abs/2110.15114 (2021) - [i27]Jinpeng Wang, Jieming Zhu, Xiuqiang He:
Cross-Batch Negative Sampling for Training Two-Tower Recommenders. CoRR abs/2110.15154 (2021) - [i26]Chenxu Zhu, Bo Chen, Weinan Zhang, Jincai Lai, Ruiming Tang, Xiuqiang He, Zhenguo Li, Yong Yu:
AIM: Automatic Interaction Machine for Click-Through Rate Prediction. CoRR abs/2111.03318 (2021) - [i25]Handong Ma, Jiawei Hou, Chenxu Zhu, Weinan Zhang, Ruiming Tang, Jincai Lai, Jieming Zhu, Xiuqiang He, Yong Yu:
QA4PRF: A Question Answering based Framework for Pseudo Relevance Feedback. CoRR abs/2111.08229 (2021) - [i24]Wei Guo, Can Zhang, Zhicheng He, Jiarui Qin, Huifeng Guo, Bo Chen, Ruiming Tang, Xiuqiang He, Rui Zhang:
MISS: Multi-Interest Self-Supervised Learning Framework for Click-Through Rate Prediction. CoRR abs/2111.15068 (2021) - [i23]Yankai Chen, Yifei Zhang, Yingxue Zhang, Huifeng Guo, Jingjie Li, Ruiming Tang, Xiuqiang He, Irwin King:
Towards Low-loss 1-bit Quantization of User-item Representations for Top-K Recommendation. CoRR abs/2112.01944 (2021) - 2020
- [j9]Feng Liu, Ruiming Tang, Huifeng Guo, Xutao Li, Yunming Ye, Xiuqiang He:
Top-aware reinforcement learning based recommendation. Neurocomputing 417: 255-269 (2020) - [j8]Feng Liu, Ruiming Tang, Xutao Li, Weinan Zhang, Yunming Ye, Haokun Chen, Huifeng Guo, Yuzhou Zhang, Xiuqiang He:
State representation modeling for deep reinforcement learning based recommendation. Knowl. Based Syst. 205: 106170 (2020) - [c45]Guibing Guo, Bowei Chen, Xiaoyan Zhang, Zhirong Liu, Zhenhua Dong, Xiuqiang He:
Leveraging Title-Abstract Attentive Semantics for Paper Recommendation. AAAI 2020: 67-74 - [c44]Zifeng Wang, Hong Zhu, Zhenhua Dong, Xiuqiang He, Shao-Lun Huang:
Less Is Better: Unweighted Data Subsampling via Influence Function. AAAI 2020: 6340-6347 - [c43]Bo Chen, Wei Guo, Ruiming Tang, Xin Xin, Yue Ding, Xiuqiang He, Dong Wang:
TGCN: Tag Graph Convolutional Network for Tag-Aware Recommendation. CIKM 2020: 155-164 - [c42]Farhan Khawar, Xu Hang, Ruiming Tang, Bin Liu, Zhenguo Li, Xiuqiang He:
AutoFeature: Searching for Feature Interactions and Their Architectures for Click-through Rate Prediction. CIKM 2020: 625-634 - [c41]Weiwen Liu, Qing Liu, Ruiming Tang, Junyang Chen, Xiuqiang He, Pheng-Ann Heng:
Personalized Re-ranking with Item Relationships for E-commerce. CIKM 2020: 925-934 - [c40]Xinyi Dai, Jiawei Hou, Qing Liu, Yunjia Xi, Ruiming Tang, Weinan Zhang, Xiuqiang He, Jun Wang, Yong Yu:
U-rank: Utility-oriented Learning to Rank with Implicit Feedback. CIKM 2020: 2373-2380 - [c39]Jieming Zhu, Jinyang Liu, Weiqi Li, Jincai Lai, Xiuqiang He, Liang Chen, Zibin Zheng:
Ensembled CTR Prediction via Knowledge Distillation. CIKM 2020: 2941-2958 - [c38]Jianing Sun, Wei Guo, Dengcheng Zhang, Yingxue Zhang, Florence Regol, Yaochen Hu, Huifeng Guo, Ruiming Tang, Han Yuan, Xiuqiang He, Mark Coates:
A Framework for Recommending Accurate and Diverse Items Using Bayesian Graph Convolutional Neural Networks. KDD 2020: 2030-2039 - [c37]Bin Liu, Chenxu Zhu, Guilin Li, Weinan Zhang, Jincai Lai, Ruiming Tang, Xiuqiang He, Zhenguo Li, Yong Yu:
AutoFIS: Automatic Feature Interaction Selection in Factorization Models for Click-Through Rate Prediction. KDD 2020: 2636-2645 - [c36]Chih-Yao Chang, Xing Tang, Bo-Wen Yuan, Jui-Yang Hsia, Zhirong Liu, Zhenhua Dong, Xiuqiang He, Chih-Jen Lin:
AutoConjunction: Adaptive Model-based Feature Conjunction for CTR Prediction. MDM 2020: 202-209 - [c35]Zhu Zhang, Zhijie Lin, Zhou Zhao, Jieming Zhu, Xiuqiang He:
Regularized Two-Branch Proposal Networks for Weakly-Supervised Moment Retrieval in Videos. ACM Multimedia 2020: 4098-4106 - [c34]Zhu Zhang, Zhou Zhao, Zhijie Lin, Jieming Zhu, Xiuqiang He:
Counterfactual Contrastive Learning for Weakly-Supervised Vision-Language Grounding. NeurIPS 2020 - [c33]Zhenhua Dong, Hong Zhu, Pengxiang Cheng, Xinhua Feng, Guohao Cai, Xiuqiang He, Jun Xu, Jirong Wen:
Counterfactual learning for recommender system. RecSys 2020: 568-569 - [c32]Rui Ding, Guibing Guo, Xiaochun Yang, Bowei Chen, Zhirong Liu, Xiuqiang He:
BiGAN: Collaborative Filtering with Bidirectional Generative Adversarial Networks. SDM 2020: 82-90 - [c31]Sijin Zhou, Xinyi Dai, Haokun Chen, Weinan Zhang, Kan Ren, Ruiming Tang, Xiuqiang He, Yong Yu:
Interactive Recommender System via Knowledge Graph-enhanced Reinforcement Learning. SIGIR 2020: 179-188 - [c30]Bin Liu, Niannan Xue, Huifeng Guo, Ruiming Tang, Stefanos Zafeiriou, Xiuqiang He, Zhenguo Li:
AutoGroup: Automatic Feature Grouping for Modelling Explicit High-Order Feature Interactions in CTR Prediction. SIGIR 2020: 199-208 - [c29]Dugang Liu, Pengxiang Cheng, Zhenhua Dong, Xiuqiang He, Weike Pan, Zhong Ming:
A General Knowledge Distillation Framework for Counterfactual Recommendation via Uniform Data. SIGIR 2020: 831-840 - [c28]Jianing Sun, Yingxue Zhang, Wei Guo, Huifeng Guo, Ruiming Tang, Xiuqiang He, Chen Ma, Mark Coates:
Neighbor Interaction Aware Graph Convolution Networks for Recommendation. SIGIR 2020: 1289-1298 - [c27]Xu Chen, Changying Du, Xiuqiang He, Jun Wang:
JIT2R: A Joint Framework for Item Tagging and Tag-based Recommendation. SIGIR 2020: 1681-1684 - [c26]Wei Guo, Can Zhang, Huifeng Guo, Ruiming Tang, Xiuqiang He:
Multi-Branch Convolutional Network for Context-Aware Recommendation. SIGIR 2020: 1709-1712 - [c25]Jiangxing Yu, Hong Zhu, Chih-Yao Chang, Xinhua Feng, Bo-Wen Yuan, Xiuqiang He, Zhenhua Dong:
Influence Function for Unbiased Recommendation. SIGIR 2020: 1929-1932 - [c24]Kelong Mao, Xi Xiao, Jieming Zhu, Biao Lu, Ruiming Tang, Xiuqiang He:
Item Tagging for Information Retrieval: A Tripartite Graph Neural Network based Approach. SIGIR 2020: 2327-2336 - [c23]Feng Liu, Huifeng Guo, Xutao Li, Ruiming Tang, Yunming Ye, Xiuqiang He:
End-to-End Deep Reinforcement Learning based Recommendation with Supervised Embedding. WSDM 2020: 384-392 - [c22]Feng Liu, Wei Guo, Huifeng Guo, Ruiming Tang, Yunming Ye, Xiuqiang He:
Dual-attentional Factorization-Machines based Neural Network for User Response Prediction. WWW (Companion Volume) 2020: 26-27 - [c21]Mi Luo, Fei Chen, Pengxiang Cheng, Zhenhua Dong, Xiuqiang He, Jiashi Feng, Zhenguo Li:
MetaSelector: Meta-Learning for Recommendation with User-Level Adaptive Model Selection. WWW 2020: 2507-2513 - [i22]Jianing Sun, Yingxue Zhang, Chen Ma, Mark Coates, Huifeng Guo, Ruiming Tang, Xiuqiang He:
Multi-Graph Convolution Collaborative Filtering. CoRR abs/2001.00267 (2020) - [i21]Mi Luo, Fei Chen, Pengxiang Cheng, Zhenhua Dong, Xiuqiang He, Jiashi Feng, Zhenguo Li:
MetaSelector: Meta-Learning for Recommendation with User-Level Adaptive Model Selection. CoRR abs/2001.10378 (2020) - [i20]Bin Liu, Chenxu Zhu, Guilin Li, Weinan Zhang, Jincai Lai, Ruiming Tang, Xiuqiang He, Zhenguo Li, Yong Yu:
AutoFIS: Automatic Feature Interaction Selection in Factorization Models for Click-Through Rate Prediction. CoRR abs/2003.11235 (2020) - [i19]Yichao Wang, Xiangyu Zhang, Zhirong Liu, Zhenhua Dong, Xinhua Feng, Ruiming Tang, Xiuqiang He:
Personalized Re-ranking for Improving Diversity in Live Recommender Systems. CoRR abs/2004.06390 (2020) - [i18]Sijin Zhou, Xinyi Dai, Haokun Chen, Weinan Zhang, Kan Ren, Ruiming Tang, Xiuqiang He, Yong Yu:
Interactive Recommender System via Knowledge Graph-enhanced Reinforcement Learning. CoRR abs/2006.10389 (2020) - [i17]Zhu Zhang, Zhijie Lin, Zhou Zhao, Jieming Zhu, Xiuqiang He:
Regularized Two-Branch Proposal Networks for Weakly-Supervised Moment Retrieval in Videos. CoRR abs/2008.08257 (2020) - [i16]Kelong Mao, Xi Xiao, Jieming Zhu, Biao Lu, Ruiming Tang, Xiuqiang He:
Item Tagging for Information Retrieval: A Tripartite Graph Neural Network based Approach. CoRR abs/2008.11567 (2020) - [i15]Yichao Wang, Huifeng Guo, Ruiming Tang, Zhirong Liu, Xiuqiang He:
A Practical Incremental Method to Train Deep CTR Models. CoRR abs/2009.02147 (2020) - [i14]Jieming Zhu, Jinyang Liu, Shuai Yang, Qi Zhang, Xiuqiang He:
FuxiCTR: An Open Benchmark for Click-Through Rate Prediction. CoRR abs/2009.05794 (2020) - [i13]Xinyi Dai, Jiawei Hou, Qing Liu, Yunjia Xi, Ruiming Tang, Weinan Zhang, Xiuqiang He, Jun Wang, Yong Yu:
U-rank: Utility-oriented Learning to Rank with Implicit Feedback. CoRR abs/2011.00550 (2020) - [i12]Jieming Zhu, Jinyang Liu, Weiqi Li, Jincai Lai, Xiuqiang He, Liang Chen, Zibin Zheng:
Ensembled CTR Prediction via Knowledge Distillation. CoRR abs/2011.04106 (2020) - [i11]Huifeng Guo, Bo Chen, Ruiming Tang, Zhenguo Li, Xiuqiang He:
AutoDis: Automatic Discretization for Embedding Numerical Features in CTR Prediction. CoRR abs/2012.08986 (2020)
2010 – 2019
- 2019
- [j7]Shoubo Hu, Bogdan Cautis, Zhitang Chen, Laiwan Chan, Yanhui Geng, Xiuqiang He:
Model-free inference of diffusion networks using RKHS embeddings. Data Min. Knowl. Discov. 33(2): 499-525 (2019) - [j6]Yanru Qu, Bohui Fang, Weinan Zhang, Ruiming Tang, Minzhe Niu, Huifeng Guo, Yong Yu, Xiuqiang He:
Product-Based Neural Networks for User Response Prediction over Multi-Field Categorical Data. ACM Trans. Inf. Syst. 37(1): 5:1-5:35 (2019) - [c20]Jianing Sun, Yingxue Zhang, Chen Ma, Mark Coates, Huifeng Guo, Ruiming Tang, Xiuqiang He:
Multi-graph Convolution Collaborative Filtering. ICDM 2019: 1306-1311 - [i10]Yi Ouyang, Bin Guo, Xing Tang, Xiuqiang He, Jian Xiong, Zhiwen Yu:
Learning Cross-Domain Representation with Multi-Graph Neural Network. CoRR abs/1905.10095 (2019) - [i9]Fajie Yuan, Xiangnan He, Guibing Guo, Zhezhao Xu, Jian Xiong, Xiuqiang He:
Modeling the Past and Future Contexts for Session-based Recommendation. CoRR abs/1906.04473 (2019) - [i8]Zifeng Wang, Hong Zhu, Zhenhua Dong, Xiuqiang He, Shao-Lun Huang:
Less Is Better: Unweighted Data Subsampling via Influence Function. CoRR abs/1912.01321 (2019) - 2018
- [c19]Feng Liu, Ruiming Tang, Xutao Li, Yunming Ye, Huifeng Guo, Xiuqiang He:
Novel Approaches to Accelerating the Convergence Rate of Markov Decision Process for Search Result Diversification. DASFAA (2) 2018: 184-200 - [c18]Weiwen Liu, Ruiming Tang, Jiajin Li, Jinkai Yu, Huifeng Guo, Xiuqiang He, Shengyu Zhang:
Field-aware probabilistic embedding neural network for CTR prediction. RecSys 2018: 412-416 - [i7]Fei Chen, Zhenhua Dong, Zhenguo Li, Xiuqiang He:
Federated Meta-Learning for Recommendation. CoRR abs/1802.07876 (2018) - [i6]Feng Liu, Ruiming Tang, Xutao Li, Yunming Ye, Huifeng Guo, Xiuqiang He:
Novel Approaches to Accelerating the Convergence Rate of Markov Decision Process for Search Result Diversification. CoRR abs/1802.08401 (2018) - [i5]Minzhe Niu, Weinan Zhang, Yanru Qu, Xuezhi Cao, Ruiming Tang, Xiuqiang He, Yong Yu:
Collaborative Filtering with Graph-based Implicit Feedback. CoRR abs/1803.03502 (2018) - [i4]Huifeng Guo, Ruiming Tang, Yunming Ye, Zhenguo Li, Xiuqiang He, Zhenhua Dong:
DeepFM: An End-to-End Wide & Deep Learning Framework for CTR Prediction. CoRR abs/1804.04950 (2018) - [i3]Yanru Qu, Bohui Fang, Weinan Zhang, Ruiming Tang, Minzhe Niu, Huifeng Guo, Yong Yu, Xiuqiang He:
Product-based Neural Networks for User Response Prediction over Multi-field Categorical Data. CoRR abs/1807.00311 (2018) - 2017
- [c17]Huifeng Guo, Ruiming Tang, Yunming Ye, Zhenguo Li, Xiuqiang He:
A Graph-Based Push Service Platform. DASFAA (2) 2017: 636-648 - [c16]Huifeng Guo, Ruiming Tang, Yunming Ye, Zhenguo Li, Xiuqiang He:
DeepFM: A Factorization-Machine based Neural Network for CTR Prediction. IJCAI 2017: 1725-1731 - [c15]Huifeng Guo, Ruiming Tang, Yunming Ye, Xiuqiang He:
Holistic Neural Network for CTR Prediction. WWW (Companion Volume) 2017: 787-788 - [i2]Huifeng Guo, Ruiming Tang, Yunming Ye, Zhenguo Li, Xiuqiang He:
DeepFM: A Factorization-Machine based Neural Network for CTR Prediction. CoRR abs/1703.04247 (2017) - 2016
- [i1]Huifeng Guo, Ruiming Tang, Yunming Ye, Zhenguo Li, Xiuqiang He:
A Graph-based Push Service Platform. CoRR abs/1611.09496 (2016) - 2015
- [c14]Xiaomin Fang, Rong Pan, Guoxiang Cao, Xiuqiang He, Wenyuan Dai:
Personalized Tag Recommendation through Nonlinear Tensor Factorization Using Gaussian Kernel. AAAI 2015: 439-445 - [c13]Xiuqiang He, Wenyuan Dai, Guoxiang Cao, Ruiming Tang, Mingxuan Yuan, Qiang Yang:
Mining target users for online marketing based on App Store data. IEEE BigData 2015: 1043-1052 - [c12]Ruiming Tang, Huayu Wu, Xiuqiang He, Stéphane Bressan:
Valuating Queries for Data Trading in Modern Cities. ICDM Workshops 2015: 414-421 - 2014
- [j5]Mingxuan Yuan, Ke Deng, Jia Zeng, Yanhua Li, Bing Ni, Xiuqiang He, Fei Wang, Wenyuan Dai, Qiang Yang:
OceanST: A Distributed Analytic System for Large-Scale Spatiotemporal Mobile Broadband Data. Proc. VLDB Endow. 7(13): 1561-1564 (2014) - 2012
- [c11]Xiuqiang He, Patrick P. C. Lee, Lujia Pan, Cheng He, John C. S. Lui:
A Panoramic View of 3G Data/Control-Plane Traffic: Mobile Device Perspective. Networking (1) 2012: 318-330 - 2010
- [j4]Xiuqiang He, Zonghua Gu, Yongxin Zhu:
Task Allocation and Optimization of Distributed Embedded Systems with Simulated Annealing and Geometric Programming. Comput. J. 53(7): 1071-1091 (2010) - [j3]Mingxuan Yuan, Zonghua Gu, Xiuqiang He, Xue Liu, Lei Jiang:
Hardware/software partitioning and pipelined scheduling on runtime reconfigurable FPGAs. ACM Trans. Design Autom. Electr. Syst. 15(2): 13:1-13:41 (2010)
2000 – 2009
- 2009
- [j2]Zonghua Gu, Weichen Liu, Jiang Xu, Jin Cui, Xiuqiang He, Qingxu Deng:
Efficient algorithms for 2D area management and online task placement on runtime reconfigurable FPGAs. Microprocess. Microsystems 33(5-6): 374-387 (2009) - 2008
- [j1]Xiuqiang He, Mingxuan Yuan, Zonghua Gu:
A Hierarchical Framework for Design Space Exploration and Optimization of TTP-Based Distributed Embedded Systems. IEEE Trans. Ind. Informatics 4(4): 237-249 (2008) - [c10]Mingxuan Yuan, Xiuqiang He, Zonghua Gu:
Hardware/Software Partitioning and Static Task Scheduling on Runtime Reconfigurable FPGAs using a SMT Solver. IEEE Real-Time and Embedded Technology and Applications Symposium 2008: 295-304 - [c9]Weichen Liu, Mingxuan Yuan, Xiuqiang He, Zonghua Gu, Xue Liu:
Efficient SAT-Based Mapping and Scheduling of Homogeneous Synchronous Dataflow Graphs for Throughput Optimization. RTSS 2008: 492-504 - 2007
- [c8]Zonghua Gu, Xiuqiang He, Mingxuan Yuan:
Optimization of Static Task and Bus Access Schedules for Time-Triggered Distributed Embedded Systems with Model-Checking. DAC 2007: 294-299 - [c7]Jin Cui, Qingxu Deng, Xiuqiang He, Zonghua Gu:
An efficient algorithm for online management of 2D area of partially reconfigurable FPGAs. DATE 2007: 129-134 - [c6]Zonghua Gu, Mingxuan Yuan, Xiuqiang He:
Optimal Static Task Scheduling on Reconfigurable Hardware Devices Using Model-Checking. IEEE Real-Time and Embedded Technology and Applications Symposium 2007: 32-44 - [c5]Zonghua Gu, Mingxuan Yuan, Nan Guan, Mingsong Lv, Xiuqiang He, Qingxu Deng, Ge Yu:
Static Scheduling and Software Synthesis for Dataflow Graphs with Symbolic Model-Checking. RTSS 2007: 353-364 - 2005
- [c4]Yinfeng Wang, Xiaoshe Dong, Xiuqiang He, Hua Guo, Fang Zheng, Zhongsheng Qin:
A Constellation Model for Grid Resource Management. APPT 2005: 263-272 - [c3]Yinfeng Wang, Xiaoshe Dong, Hua Guo, Xiuqiang He, GuoRong Liu:
A Constellation Resource Discovery Model Based on Scalable Multi-tape Universal Turing Machine. GCC 2005: 633-644 - [c2]Xiaoshe Dong, Yinfeng Wang, Xiuqiang He, Hua Guo, Fang Zheng, Weiguo Wu:
The Campus Resource Management Based on Constellation Model in the ChinaGrid. ISPA Workshops 2005: 249-256 - [c1]Xiaoshe Dong, Xiuqiang He, Hua Guo, Wancheng Li, Xingjun Zhang:
Construction of Overlay Network in P2P-based Resource Discovery Model in Grid Environment. SKG 2005: 27
Coauthor Index
[j22] [j21] [j19] [j15] [j13] [c77] [c76] [c75] [c73] [c72] [c71] [i47] [i46] [i44] [j12] [c63] [c61] [c59] [c58] [c57] [c52] [c51] [c46] [i41] [i40] [i39] [i38] [i37] [i36] [i35] [i30] [i29] [i26] [i25] [i24] [i23] [j9] [j8] [c43] [c42] [c41] [c40] [c38] [c37] [c31] [c30] [c28] [c26] [c24] [c23] [c22] [i22] [i20] [i19] [i18] [i16] [i15] [i13] [i11] [j6] [c20] [c19] [c18] [i6] [i5] [i4] [i3] [c17] [c16] [c15] [i2] [i1] [c13] [c12]
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