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ORCIDXiuqiang He 0001
XiuQiang He 0001
Person information
- affiliation: 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: 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://dblp1.uni-trier.de/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
- 2023
[j17]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)- [j16]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) - [c82]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 - [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 - [i54]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) - [i53]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) - [i52]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) - [i51]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) - [i50]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) - 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]