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2020 – today
- 2024
- [j12]Shiwei Li, Huifeng Guo, Xing Tang, Ruiming Tang, Lu Hou, Ruixuan Li, Rui Zhang:
Embedding Compression in Recommender Systems: A Survey. ACM Comput. Surv. 56(5): 130:1-130:21 (2024) - [j11]Ziru Liu, Kecheng Chen, Fengyi Song, Bo Chen, Xiangyu Zhao, Huifeng Guo, Ruiming Tang:
AutoAssign+: Automatic Shared Embedding Assignment in streaming recommendation. Knowl. Inf. Syst. 66(1): 89-113 (2024) - [j10]Zehui Mao, Huan Wang, Bin Jiang, Juan Xu, Huifeng Guo:
Graph Convolutional Neural Network for Intelligent Fault Diagnosis of Machines via Knowledge Graph. IEEE Trans. Ind. Informatics 20(5): 7862-7870 (2024) - [j9]Bo Chen, Xiangyu Zhao, Yejing Wang, Wenqi Fan, Huifeng Guo, Ruiming Tang:
A Comprehensive Survey on Automated Machine Learning for Recommendations. Trans. Recomm. Syst. 2(2): 13:1-13:38 (2024) - [c59]Pengyue Jia, Yichao Wang, Shanru Lin, Xiaopeng Li, Xiangyu Zhao, Huifeng Guo, Ruiming Tang:
D3: A Methodological Exploration of Domain Division, Modeling, and Balance in Multi-Domain Recommendations. AAAI 2024: 8553-8561 - [c58]Jingtong Gao, Bo Chen, Menghui Zhu, Xiangyu Zhao, Xiaopeng Li, Yuhao Wang, Yichao Wang, Huifeng Guo, Ruiming Tang:
HierRec: Scenario-Aware Hierarchical Modeling for Multi-scenario Recommendations. CIKM 2024: 653-662 - [c57]Yuening Wang, Man Chen, Yaochen Hu, Wei Guo, Yingxue Zhang, Huifeng Guo, Yong Liu, Mark Coates:
Enhancing Click-through Rate Prediction in Recommendation Domain with Search Query Representation. CIKM 2024: 2462-2471 - [c56]Yuhao Wang, Yichao Wang, Zichuan Fu, Xiangyang Li, Wanyu Wang, Yuyang Ye, Xiangyu Zhao, Huifeng Guo, Ruiming Tang:
LLM4MSR: An LLM-Enhanced Paradigm for Multi-Scenario Recommendation. CIKM 2024: 2472-2481 - [c55]Pengyue Jia, Yejing Wang, Zhaocheng Du, Xiangyu Zhao, Yichao Wang, Bo Chen, Wanyu Wang, Huifeng Guo, Ruiming Tang:
ERASE: Benchmarking Feature Selection Methods for Deep Recommender Systems. KDD 2024: 5194-5205 - [c54]Yang Yang, Bo Chen, Chenxu Zhu, Menghui Zhu, Xinyi Dai, Huifeng Guo, Muyu Zhang, Zhenhua Dong, Ruiming Tang:
AIE: Auction Information Enhanced Framework for CTR Prediction in Online Advertising. RecSys 2024: 633-642 - [c53]Yuhao Wang, Ziru Liu, Yichao Wang, Xiangyu Zhao, Bo Chen, Huifeng Guo, Ruiming Tang:
Diff-MSR: A Diffusion Model Enhanced Paradigm for Cold-Start Multi-Scenario Recommendation. WSDM 2024: 779-787 - [c52]Zirui Zhu, Yong Liu, Zangwei Zheng, Huifeng Guo, Yang You:
Helen: Optimizing CTR Prediction Models with Frequency-wise Hessian Eigenvalue Regularization. WWW 2024: 3485-3496 - [i43]Zirui Zhu, Yong Liu, Zangwei Zheng, Huifeng Guo, Yang You:
Helen: Optimizing CTR Prediction Models with Frequency-wise Hessian Eigenvalue Regularization. CoRR abs/2403.00798 (2024) - [i42]Pengyue Jia, Yejing Wang, Zhaocheng Du, Xiangyu Zhao, Yichao Wang, Bo Chen, Wanyu Wang, Huifeng Guo, Ruiming Tang:
ERASE: Benchmarking Feature Selection Methods for Deep Recommender Systems. CoRR abs/2403.12660 (2024) - [i41]Wenlin Zhang, Chuhan Wu, Xiangyang Li, Yuhao Wang, Kuicai Dong, Yichao Wang, Xinyi Dai, Xiangyu Zhao, Huifeng Guo, Ruiming Tang:
Tired of Plugins? Large Language Models Can Be End-To-End Recommenders. CoRR abs/2404.00702 (2024) - [i40]Jingtong Gao, Bo Chen, Xiangyu Zhao, Weiwen Liu, Xiangyang Li, Yichao Wang, Zijian Zhang, Wanyu Wang, Yuyang Ye, Shanru Lin, Huifeng Guo, Ruiming Tang:
LLM-enhanced Reranking in Recommender Systems. CoRR abs/2406.12433 (2024) - [i39]Yuhao Wang, Yichao Wang, Zichuan Fu, Xiangyang Li, Xiangyu Zhao, Huifeng Guo, Ruiming Tang:
LLM4MSR: An LLM-Enhanced Paradigm for Multi-Scenario Recommendation. CoRR abs/2406.12529 (2024) - [i38]Bo Chen, Xinyi Dai, Huifeng Guo, Wei Guo, Weiwen Liu, Yong Liu, Jiarui Qin, Ruiming Tang, Yichao Wang, Chuhan Wu, Yaxiong Wu, Hao Zhang:
All Roads Lead to Rome: Unveiling the Trajectory of Recommender Systems Across the LLM Era. CoRR abs/2407.10081 (2024) - [i37]Shiwei Li, Huifeng Guo, Xing Tang, Ruiming Tang, Lu Hou, Ruixuan Li, Rui Zhang:
Embedding Compression in Recommender Systems: A Survey. CoRR abs/2408.02304 (2024) - [i36]Yusheng Lu, Zhaocheng Du, Xiangyang Li, Xiangyu Zhao, Weiwen Liu, Yichao Wang, Huifeng Guo, Ruiming Tang, Zhenhua Dong, Yongrui Duan:
Prompt Tuning as User Inherent Profile Inference Machine. CoRR abs/2408.06577 (2024) - [i35]Yang Yang, Bo Chen, Chenxu Zhu, Menghui Zhu, Xinyi Dai, Huifeng Guo, Muyu Zhang, Zhenhua Dong, Ruiming Tang:
AIE: Auction Information Enhanced Framework for CTR Prediction in Online Advertising. CoRR abs/2408.07907 (2024) - [i34]Yuening Wang, Chen Ma, Yaochen Hu, Wei Guo, Yingxue Zhang, Huifeng Guo, Yong Liu, Mark Coates:
Enhancing CTR Prediction in Recommendation Domain with Search Query Representation. CoRR abs/2410.21487 (2024) - 2023
- [c51]Shiwei Li, Huifeng Guo, Lu Hou, Wei Zhang, Xing Tang, Ruiming Tang, Rui Zhang, Ruixuan Li:
Adaptive Low-Precision Training for Embeddings in Click-Through Rate Prediction. AAAI 2023: 4435-4443 - [c50]Huan Wang, Huifeng Guo, Zehui Mao, Haibin Li, Qiang Qu, Yulei Yang:
Bidirectional Mapping RTE for Fault Knowledge Graph Construction. SAFEPROCESS 2023: 1-6 - [c49]Xiaopeng Li, Fan Yan, Xiangyu Zhao, Yichao Wang, Bo Chen, Huifeng Guo, Ruiming Tang:
HAMUR: Hyper Adapter for Multi-Domain Recommendation. CIKM 2023: 1268-1277 - [c48]Qidong Liu, Fan Yan, Xiangyu Zhao, Zhaocheng Du, Huifeng Guo, Ruiming Tang, Feng Tian:
Diffusion Augmentation for Sequential Recommendation. CIKM 2023: 1576-1586 - [c47]Wei Guo, Chenxu Zhu, Fan Yan, Bo Chen, Weiwen Liu, Huifeng Guo, Hongkun Zheng, Yong Liu, Ruiming Tang:
DFFM: Domain Facilitated Feature Modeling for CTR Prediction. CIKM 2023: 4602-4608 - [c46]Chang Meng, Hengyu Zhang, Wei Guo, Huifeng Guo, Haotian Liu, Yingxue Zhang, Hongkun Zheng, Ruiming Tang, Xiu Li, Rui Zhang:
Hierarchical Projection Enhanced Multi-behavior Recommendation. KDD 2023: 4649-4660 - [c45]Yejing Wang, Zhaocheng Du, Xiangyu Zhao, Bo Chen, Huifeng Guo, Ruiming Tang, Zhenhua Dong:
Single-shot Feature Selection for Multi-task Recommendations. SIGIR 2023: 341-351 - [c44]Jingtong Gao, Xiangyu Zhao, Bo Chen, Fan Yan, Huifeng Guo, Ruiming Tang:
AutoTransfer: Instance Transfer for Cross-Domain Recommendations. SIGIR 2023: 1478-1487 - [c43]Yuhao Wang, Xiangyu Zhao, Bo Chen, Qidong Liu, Huifeng Guo, Huanshuo Liu, Yichao Wang, Rui Zhang, Ruiming Tang:
PLATE: A Prompt-Enhanced Paradigm for Multi-Scenario Recommendations. SIGIR 2023: 1498-1507 - [c42]Chenxu Zhu, Bo Chen, Huifeng Guo, Hang Xu, Xiangyang Li, Xiangyu Zhao, Weinan Zhang, Yong Yu, Ruiming Tang:
AutoGen: An Automated Dynamic Model Generation Framework for Recommender System. WSDM 2023: 598-606 - [c41]Ruiming Tang, Bo Chen, Yejing Wang, Huifeng Guo, Yong Liu, Wenqi Fan, Xiangyu Zhao:
AutoML for Deep Recommender Systems: Fundamentals and Advances. WSDM 2023: 1264-1267 - [c40]Wei Guo, Chang Meng, Enming Yuan, Zhicheng He, Huifeng Guo, Yingxue Zhang, Bo Chen, Yaochen Hu, Ruiming Tang, Xiu Li, Rui Zhang:
Compressed Interaction Graph based Framework for Multi-behavior Recommendation. WWW 2023: 960-970 - [i33]Yuhao Wang, Ha Tsz Lam, Yi Wong, Ziru Liu, Xiangyu Zhao, Yichao Wang, Bo Chen, Huifeng Guo, Ruiming Tang:
Multi-Task Deep Recommender Systems: A Survey. CoRR abs/2302.03525 (2023) - [i32]Wei Guo, Chang Meng, Enming Yuan, Zhicheng He, Huifeng Guo, Yingxue Zhang, Bo Chen, Yaochen Hu, Ruiming Tang, Xiu Li, Rui Zhang:
Compressed Interaction Graph based Framework for Multi-behavior Recommendation. CoRR abs/2303.02418 (2023) - [i31]Jianghao Lin, Xinyi Dai, Yunjia Xi, Weiwen Liu, Bo Chen, Xiangyang Li, Chenxu Zhu, Huifeng Guo, Yong Yu, Ruiming Tang, Weinan Zhang:
How Can Recommender Systems Benefit from Large Language Models: A Survey. CoRR abs/2306.05817 (2023) - [i30]Ziru Liu, Kecheng Chen, Fengyi Song, Bo Chen, Xiangyu Zhao, Huifeng Guo, Ruiming Tang:
AutoAssign+: Automatic Shared Embedding Assignment in Streaming Recommendation. CoRR abs/2308.06965 (2023) - [i29]Hengyu Zhang, Chang Meng, Wei Guo, Huifeng Guo, Jieming Zhu, Guangpeng Zhao, Ruiming Tang, Xiu Li:
Time-aligned Exposure-enhanced Model for Click-Through Rate Prediction. CoRR abs/2308.09966 (2023) - [i28]Jingtong Gao, Bo Chen, Menghui Zhu, Xiangyu Zhao, Xiaopeng Li, Yuhao Wang, Yichao Wang, Huifeng Guo, Ruiming Tang:
Scenario-Aware Hierarchical Dynamic Network for Multi-Scenario Recommendation. CoRR abs/2309.02061 (2023) - [i27]Xiaopeng Li, Fan Yan, Xiangyu Zhao, Yichao Wang, Bo Chen, Huifeng Guo, Ruiming Tang:
HAMUR: Hyper Adapter for Multi-Domain Recommendation. CoRR abs/2309.06217 (2023) - [i26]Qidong Liu, Fan Yan, Xiangyu Zhao, Zhaocheng Du, Huifeng Guo, Ruiming Tang, Feng Tian:
Diffusion Augmentation for Sequential Recommendation. CoRR abs/2309.12858 (2023) - [i25]Zichuan Fu, Xiangyang Li, Chuhan Wu, Yichao Wang, Kuicai Dong, Xiangyu Zhao, Mengchen Zhao, Huifeng Guo, Ruiming Tang:
A Unified Framework for Multi-Domain CTR Prediction via Large Language Models. CoRR abs/2312.10743 (2023) - 2022
- [j8]Niannan Xue, Bin Liu, Huifeng Guo, Ruiming Tang, Fengwei Zhou, Stefanos Zafeiriou, Yuzhou Zhang, Jun Wang, Zhenguo Li:
AutoHash: Learning Higher-Order Feature Interactions for Deep CTR Prediction. IEEE Trans. Knowl. Data Eng. 34(6): 2653-2666 (2022) - [c39]Fuyuan Lyu, Xing Tang, Hong Zhu, Huifeng Guo, Yingxue Zhang, Ruiming Tang, Xue Liu:
OptEmbed: Learning Optimal Embedding Table for Click-through Rate Prediction. CIKM 2022: 1399-1409 - [c38]Hengyu Zhang, Enming Yuan, Wei Guo, Zhicheng He, Jiarui Qin, Huifeng Guo, Bo Chen, Xiu Li, Ruiming Tang:
Disentangling Past-Future Modeling in Sequential Recommendation via Dual Networks. CIKM 2022: 2549-2558 - [c37]Bo Chen, Huifeng Guo, Weiwen Liu, Yue Ding, Yunzhe Li, Wei Guo, Yichao Wang, Zhicheng He, Ruiming Tang, Rui Zhang:
Numerical Feature Representation with Hybrid N-ary Encoding. CIKM 2022: 2984-2993 - [c36]Xiangyang Li, Bo Chen, Huifeng Guo, Jingjie Li, Chenxu Zhu, Xiang Long, Sujian Li, Yichao Wang, Wei Guo, Longxia Mao, Jinxing Liu, Zhenhua Dong, Ruiming Tang:
IntTower: The Next Generation of Two-Tower Model for Pre-Ranking System. CIKM 2022: 3292-3301 - [c35]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 - [c34]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 - [c33]Fengyi Song, Bo Chen, Xiangyu Zhao, Huifeng Guo, Ruiming Tang:
AutoAssign: Automatic Shared Embedding Assignment in Streaming Recommendation. ICDM 2022: 458-467 - [c32]Yankai Chen, Yifei Zhang, Huifeng Guo, Ruiming Tang, Irwin King:
An Effective Post-training Embedding Binarization Approach for Fast Online Top-K Passage Matching. AACL/IJCNLP (2) 2022: 102-108 - [c31]Yankai Chen, Huifeng Guo, Yingxue Zhang, Chen Ma, Ruiming Tang, Jingjie Li, Irwin King:
Learning Binarized Graph Representations with Multi-faceted Quantization Reinforcement for Top-K Recommendation. KDD 2022: 168-178 - [c30]Zhicheng He, Wei Xia, Kai Dong, Huifeng Guo, Ruiming Tang, Dingyin Xia, Rui Zhang:
Unsupervised Learning Style Classification for Learning Path Generation in Online Education Platforms. KDD 2022: 2997-3006 - [c29]Yichao Wang, Huifeng Guo, Bo Chen, Weiwen Liu, Zhirong Liu, Qi Zhang, Zhicheng He, Hongkun Zheng, Weiwei Yao, Muyu Zhang, Zhenhua Dong, Ruiming Tang:
CausalInt: Causal Inspired Intervention for Multi-Scenario Recommendation. KDD 2022: 4090-4099 - [c28]Enming Yuan, Wei Guo, Zhicheng He, Huifeng Guo, Chengkai Liu, Ruiming Tang:
Multi-Behavior Sequential Transformer Recommender. SIGIR 2022: 1642-1652 - [c27]Riccardo Tommasini, Senjuti Basu Roy, Xuan Wang, Hongwei Wang, Heng Ji, Jiawei Han, Preslav Nakov, Giovanni Da San Martino, Firoj Alam, Markus Schedl, Elisabeth Lex, Akash Bharadwaj, Graham Cormode, Milan Dojchinovski, Jan Forberg, Johannes Frey, Pieter Bonte, Marco Balduini, Matteo Belcao, Emanuele Della Valle, Junliang Yu, Hongzhi Yin, Tong Chen, Haochen Liu, Yiqi Wang, Wenqi Fan, Xiaorui Liu, Jamell Dacon, Lingjuan Lye, Jiliang Tang, Aristides Gionis, Stefan Neumann, Bruno Ordozgoiti, Simon Razniewski, Hiba Arnaout, Shrestha Ghosh, Fabian M. Suchanek, Lingfei Wu, Yu Chen, Yunyao Li, Bang Liu, Filip Ilievski, Daniel Garijo, Hans Chalupsky, Pedro A. Szekely, Ilias Kanellos, Dimitris Sacharidis, Thanasis Vergoulis, Nurendra Choudhary, Nikhil Rao, Karthik Subbian, Srinivasan H. Sengamedu, Chandan K. Reddy, Friedhelm Victor, Bernhard Haslhofer, George Katsogiannis-Meimarakis, Georgia Koutrika, Shengmin Jin, Danai Koutra, Reza Zafarani, Yulia Tsvetkov, Vidhisha Balachandran, Sachin Kumar, Xiangyu Zhao, Bo Chen, Huifeng Guo, Yejing Wang, Ruiming Tang, Yang Zhang, Wenjie Wang, Peng Wu, Fuli Feng, Xiangnan He:
Accepted Tutorials at The Web Conference 2022. WWW (Companion Volume) 2022: 391-399 - [i24]Bo Chen, Xiangyu Zhao, Yejing Wang, Wenqi Fan, Huifeng Guo, Ruiming Tang:
Automated Machine Learning for Deep Recommender Systems: A Survey. CoRR abs/2204.01390 (2022) - [i23]Yankai Chen, Huifeng Guo, Yingxue Zhang, Chen Ma, Ruiming Tang, Jingjie Li, Irwin King:
Learning Binarized Graph Representations with Multi-faceted Quantization Reinforcement for Top-K Recommendation. CoRR abs/2206.02115 (2022) - [i22]Fuyuan Lyu, Xing Tang, Hong Zhu, Huifeng Guo, Yingxue Zhang, Ruiming Tang, Xue Liu:
OptEmbed: Learning Optimal Embedding Table for Click-through Rate Prediction. CoRR abs/2208.04482 (2022) - [i21]Xiangyang Li, Bo Chen, Huifeng Guo, Jingjie Li, Chenxu Zhu, Xiang Long, Sujian Li, Yichao Wang, Wei Guo, Longxia Mao, Jinxing Liu, Zhenhua Dong, Ruiming Tang:
IntTower: the Next Generation of Two-Tower Model for Pre-Ranking System. CoRR abs/2210.09890 (2022) - [i20]Hengyu Zhang, Enming Yuan, Wei Guo, Zhicheng He, Jiarui Qin, Huifeng Guo, Bo Chen, Xiu Li, Ruiming Tang:
Disentangling Past-Future Modeling in Sequential Recommendation via Dual Networks. CoRR abs/2210.14577 (2022) - [i19]Shiwei Li, Huifeng Guo, Lu Hou, Wei Zhang, Xing Tang, Ruiming Tang, Rui Zhang, Ruixuan Li:
Adaptive Low-Precision Training for Embeddings in Click-Through Rate Prediction. CoRR abs/2212.05735 (2022) - 2021
- [c26]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 - [c25]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 - [c24]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 - [c23]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 - [i18]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) - [i17]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) - [i16]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) - [i15]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) - [i14]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) - [i13]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
- [j7]Feng Liu, Ruiming Tang, Huifeng Guo, Xutao Li, Yunming Ye, Xiuqiang He:
Top-aware reinforcement learning based recommendation. Neurocomputing 417: 255-269 (2020) - [j6]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) - [c22]Hui Yang, Jingwen Nan, Qiuyan Yao, Bowen Bao, Yong Jiang, Huifeng Guo:
Representation Learning-based Slice Resource Reconfiguring Scheme in Multimedia Networks. BMSB 2020: 1-3 - [c21]Yishi Xu, Yingxue Zhang, Wei Guo, Huifeng Guo, Ruiming Tang, Mark Coates:
GraphSAIL: Graph Structure Aware Incremental Learning for Recommender Systems. CIKM 2020: 2861-2868 - [c20]Chao Li, Hui Yang, Bowen Bao, Huifeng Guo, Yong Jiang, Jie Zhang:
Spearman Correlation Coefficient Abnormal Behavior Monitoring Technology Based on RNN in 5G Network for Smart City. IWCMC 2020: 1440-1442 - [c19]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 - [c18]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 - [c17]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 - [c16]Wei Guo, Can Zhang, Huifeng Guo, Ruiming Tang, Xiuqiang He:
Multi-Branch Convolutional Network for Context-Aware Recommendation. SIGIR 2020: 1709-1712 - [c15]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 - [c14]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 - [i12]Jianing Sun, Yingxue Zhang, Chen Ma, Mark Coates, Huifeng Guo, Ruiming Tang, Xiuqiang He:
Multi-Graph Convolution Collaborative Filtering. CoRR abs/2001.00267 (2020) - [i11]Yishi Xu, Yingxue Zhang, Wei Guo, Huifeng Guo, Ruiming Tang, Mark Coates:
GraphSAIL: Graph Structure Aware Incremental Learning for Recommender Systems. CoRR abs/2008.13517 (2020) - [i10]Yichao Wang, Huifeng Guo, Ruiming Tang, Zhirong Liu, Xiuqiang He:
A Practical Incremental Method to Train Deep CTR Models. CoRR abs/2009.02147 (2020) - [i9]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
- [j5]Ao Yu, Hui Yang, Qiuyan Yao, Yajie Li, Huifeng Guo, Tao Peng, Haibin Li, Jie Zhang:
Accurate Fault Location Using Deep Belief Network for Optical Fronthaul Networks in 5G and Beyond. IEEE Access 7: 77932-77943 (2019) - [j4]Ao Yu, Jie Zhang, Hui Yang, Ting Xu, Baoguo Yu, Qiuyan Yao, Yajie Li, Tao Peng, Huifeng Guo, Jun Li:
Long-Term Traffic Scheduling Based on Stacked Bidirectional Recurrent Neural Networks in Inter-Datacenter Optical Networks. IEEE Access 7: 182296-182308 (2019) - [j3]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) - [c13]Jianing Sun, Yingxue Zhang, Chen Ma, Mark Coates, Huifeng Guo, Ruiming Tang, Xiuqiang He:
Multi-graph Convolution Collaborative Filtering. ICDM 2019: 1306-1311 - [c12]Jingwen Nan, Hui Yang, Ao Yu, Yajie Li, Huifeng Guo, Tao Peng, Jie Zhang:
Slice-Scaling Strategy Based on Representation Learning in Flex-Grid Optical Networks. OFC 2019: 1-3 - [c11]Ao Yu, Hui Yang, Qiuyan Yao, Yajie Li, Huifeng Guo, Tao Peng, Haibin Li, Jie Zhang:
Scheduling with Flow Prediction Based on Time and Frequency 2D Classification for Hybrid Electrical/Optical Intra-Datacenter Networks. OFC 2019: 1-3 - [c10]Xudong Zhao, Hui Yang, Huifeng Guo, Tao Peng, Jie Zhang:
Accurate Fault Location based on Deep Neural Evolution Network in Optical Networks for 5G and Beyond. OFC 2019: 1-3 - [c9]Huifeng Guo, Ruiming Tang, Yunming Ye, Feng Liu, Yuzhou Zhang:
A Novel KNN Approach for Session-Based Recommendation. PAKDD (2) 2019: 381-393 - [c8]Huifeng Guo, Jinkai Yu, Qing Liu, Ruiming Tang, Yuzhou Zhang:
PAL: a position-bias aware learning framework for CTR prediction in live recommender systems. RecSys 2019: 452-456 - [c7]Wei Guo, Ruiming Tang, Huifeng Guo, Jianhua Han, Wen Yang, Yuzhou Zhang:
Order-aware Embedding Neural Network for CTR Prediction. SIGIR 2019: 1121-1124 - [c6]Bin Liu, Ruiming Tang, Yingzhi Chen, Jinkai Yu, Huifeng Guo, Yuzhou Zhang:
Feature Generation by Convolutional Neural Network for Click-Through Rate Prediction. WWW 2019: 1119-1129 - [i8]Bin Liu, Ruiming Tang, Yingzhi Chen, Jinkai Yu, Huifeng Guo, Yuzhou Zhang:
Feature Generation by Convolutional Neural Network for Click-Through Rate Prediction. CoRR abs/1904.04447 (2019) - 2018
- [c5]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 - [c4]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]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) - [i6]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) - [i5]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) - [i4]Huifeng Guo, Ruiming Tang, Yunming Ye, Feng Liu, Yuzhou Zhang:
An Adjustable Heat Conduction based KNN Approach for Session-based Recommendation. CoRR abs/1807.05739 (2018) - [i3]Feng Liu, Ruiming Tang, Xutao Li, Yunming Ye, Haokun Chen, Huifeng Guo, Yuzhou Zhang:
Deep Reinforcement Learning based Recommendation with Explicit User-Item Interactions Modeling. CoRR abs/1810.12027 (2018) - 2017
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