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2020 – today
- 2024
[j13]Chang Meng, Ziqi Zhao, Wei Guo, Yingxue Zhang, Haolun Wu, Chen Gao, Dong Li, Xiu Li, Ruiming Tang:
Coarse-to-Fine Knowledge-Enhanced Multi-Interest Learning Framework for Multi-Behavior Recommendation. ACM Trans. Inf. Syst. 42(1): 30:1-30:27 (2024)- 2023
- [j12]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) - [j11]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) - [j10]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) - [c122]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 - [c121]Yuening Wang, Yingxue Zhang, Antonios Valkanas, Ruiming Tang, Chen Ma, Jianye Hao, Mark Coates:
Structure Aware Incremental Learning with Personalized Imitation Weights for Recommender Systems. AAAI 2023: 4711-4719 - [c120]Xianyu Chen, Jian Shen, Wei Xia, Jiarui Jin, Yakun Song, Weinan Zhang, Weiwen Liu, Menghui Zhu, Ruiming Tang, Kai Dong, Dingyin Xia, Yong Yu:
Set-to-Sequence Ranking-Based Concept-Aware Learning Path Recommendation. AAAI 2023: 5027-5035 - [c119]Bowei He, Xu He, Renrui Zhang, Yingxue Zhang, Ruiming Tang, Chen Ma:
Dynamic Embedding Size Search with Minimum Regret for Streaming Recommender System. CIKM 2023: 741-750 - [c118]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 - [c117]Qingyao Li, Wei Xia, Li'ang Yin, Jian Shen, Renting Rui, Weinan Zhang, Xianyu Chen, Ruiming Tang, Yong Yu:
Graph Enhanced Hierarchical Reinforcement Learning for Goal-oriented Learning Path Recommendation. CIKM 2023: 1318-1327 - [c116]Qidong Liu, Fan Yan, Xiangyu Zhao, Zhaocheng Du, Huifeng Guo, Ruiming Tang, Feng Tian:
Diffusion Augmentation for Sequential Recommendation. CIKM 2023: 1576-1586 - [c115]Mingjia Yin, Hao Wang, Xiang Xu, Likang Wu, Sirui Zhao, Wei Guo, Yong Liu, Ruiming Tang, Defu Lian, Enhong Chen:
APGL4SR: A Generic Framework with Adaptive and Personalized Global Collaborative Information in Sequential Recommendation. CIKM 2023: 3009-3019 - [c114]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 - [c113]Weitong Ou, Bo Chen, Weiwen Liu, Xinyi Dai, Weinan Zhang, Wei Xia, Xuan Li, Ruiming Tang, Yong Yu:
Optimal Real-Time Bidding Strategy for Position Auctions in Online Advertising. CIKM 2023: 4766-4772 - [c112]Weiwen Liu, Yunjia Xi, Jiarui Qin, Xinyi Dai, Ruiming Tang, Shuai Li, Weinan Zhang, Rui Zhang:
Personalized Diversification for Neural Re-ranking in Recommendation. ICDE 2023: 802-815 - [c111]Haolun Wu, Yingxue Zhang, Chen Ma, Wei Guo, Ruiming Tang, Xue Liu, Mark Coates:
Intent-aware Multi-source Contrastive Alignment for Tag-enhanced Recommendation. ICDE 2023: 1112-1125 - [c110]Zhicheng He, Weiwen Liu, Wei Guo, Jiarui Qin, Yingxue Zhang, Yaochen Hu, Ruiming Tang:
A Survey on User Behavior Modeling in Recommender Systems. IJCAI 2023: 6656-6664 - [c109]Jianghao Lin, Yanru Qu, Wei Guo, Xinyi Dai, Ruiming Tang, Yong Yu, Weinan Zhang:
MAP: A Model-agnostic Pretraining Framework for Click-through Rate Prediction. KDD 2023: 1384-1395 - [c108]Hangyu Wang, Ting Long, Liang Yin, Weinan Zhang, Wei Xia, Qichen Hong, Dingyin Xia, Ruiming Tang, Yong Yu:
GMOCAT: A Graph-Enhanced Multi-Objective Method for Computerized Adaptive Testing. KDD 2023: 2279-2289 - [c107]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 - [c106]Weitong Ou, Bo Chen, Yingxuan Yang, Xinyi Dai, Weiwen Liu, Weinan Zhang, Ruiming Tang, Yong Yu:
Deep Landscape Forecasting in Multi-Slot Real-Time Bidding. KDD 2023: 4685-4695 - [c105]Yunjia Xi, Weiwen Liu, Yang Wang, Ruiming Tang, Weinan Zhang, Yue Zhu, Rui Zhang, Yong Yu:
On-device Integrated Re-ranking with Heterogeneous Behavior Modeling. KDD 2023: 5225-5236 - [c104]Jieming Zhu, Guohao Cai, Junjie Huang, Zhenhua Dong, Ruiming Tang, Weinan Zhang:
ReLoop2: Building Self-Adaptive Recommendation Models via Responsive Error Compensation Loop. KDD 2023: 5728-5738 - [c103]Jing Wang, Mengchen Zhao, Wei Xia, Zhenhua Dong, Ruiming Tang, Rui Zhang, Jianye Hao, Guangyong Chen, Pheng-Ann Heng:
RLMixer: A Reinforcement Learning Approach for Integrated Ranking with Contrastive User Preference Modeling. PAKDD (3) 2023: 400-413 - [c102]Yujun Li, Xing Tang, Bo Chen, Yimin Huang, Ruiming Tang, Zhenguo Li:
AutoOpt: Automatic Hyperparameter Scheduling and Optimization for Deep Click-through Rate Prediction. RecSys 2023: 183-194 - [c101]Ruiming Tang, Xiaoqiang Zhu, Junfeng Ge, Kuang-chih Lee, Biye Jiang, Xingxing Wang, Han Zhu, Tao Zhuang, Weiwen Liu, Kan Ren, Weinan Zhang, Xiangyu Zhao:
International Workshop on Deep Learning Practice for High-Dimensional Sparse Data with RecSys 2023. RecSys 2023: 1276-1280 - [c100]Weiwen Liu, Wei Guo, Yong Liu, Ruiming Tang, Hao Wang:
User Behavior Modeling with Deep Learning for Recommendation: Recent Advances. RecSys 2023: 1286-1287 - [c99]Chuhan Wu, Qinglin Jia, Zhenhua Dong, Ruiming Tang:
Customer Lifetime Value Prediction: Towards the Paradigm Shift of Recommender System Objectives. RecSys 2023: 1293-1294 - [c98]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 - [c97]Liangcai Su, Fan Yan, Jieming Zhu, Xi Xiao, Haoyi Duan, Zhou Zhao, Zhenhua Dong, Ruiming Tang:
Beyond Two-Tower Matching: Learning Sparse Retrievable Cross-Interactions for Recommendation. SIGIR 2023: 548-557 - [c96]Jingtong Gao, Xiangyu Zhao, Bo Chen, Fan Yan, Huifeng Guo, Ruiming Tang:
AutoTransfer: Instance Transfer for Cross-Domain Recommendations. SIGIR 2023: 1478-1487 - [c95]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 - [c94]Jieming Zhu, Qinglin Jia, Guohao Cai, Quanyu Dai, Jingjie Li, Zhenhua Dong, Ruiming Tang, Rui Zhang:
FINAL: Factorized Interaction Layer for CTR Prediction. SIGIR 2023: 2006-2010 - [c93]Zhiheng Zhang, Quanyu Dai, Xu Chen, Zhenhua Dong, Ruiming Tang:
Robust Causal Inference for Recommender System to Overcome Noisy Confounders. SIGIR 2023: 2349-2353 - [c92]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 - [c91]Lingyue Fu, Jianghao Lin, Weiwen Liu, Ruiming Tang, Weinan Zhang, Rui Zhang, Yong Yu:
An F-shape Click Model for Information Retrieval on Multi-block Mobile Pages. WSDM 2023: 1057-1065 - [c90]Yunjia Xi, Jianghao Lin, Weiwen Liu, Xinyi Dai, Weinan Zhang, Rui Zhang, Ruiming Tang, Yong Yu:
A Bird's-eye View of Reranking: From List Level to Page Level. WSDM 2023: 1075-1083 - [c89]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 - [c88]Menghui Zhu, Wei Xia, Weiwen Liu, Yifan Liu, Ruiming Tang, Weinan Zhang:
Integrated Ranking for News Feed with Reinforcement Learning. WWW (Companion Volume) 2023: 480-484 - [c87]Xiaofan Liu, Qinglin Jia, Chuhan Wu, Jingjie Li, Quanyu Dai, Lin Bo, Rui Zhang, Ruiming Tang:
Task Adaptive Multi-learner Network for Joint CTR and CVR Estimation. WWW (Companion Volume) 2023: 490-494 - [c86]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 - [c85]Bowei He, Xu He, Yingxue Zhang, Ruiming Tang, Chen Ma:
Dynamically Expandable Graph Convolution for Streaming Recommendation. WWW 2023: 1457-1467 - [i84]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) - [i83]Zhicheng He, Weiwen Liu, Wei Guo, Jiarui Qin, Yingxue Zhang, Yaochen Hu, Ruiming Tang:
A Survey on User Behavior Modeling in Recommender Systems. CoRR abs/2302.11087 (2023) - [i82]Xu Chen, Jingsen Zhang, Lei Wang, Quanyu Dai, Zhenhua Dong, Ruiming Tang, Rui Zhang, Li Chen, Ji-Rong Wen:
REASONER: An Explainable Recommendation Dataset with Multi-aspect Real User Labeled Ground Truths Towards more Measurable Explainable Recommendation. CoRR abs/2303.00168 (2023) - [i81]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) - [i80]Bowei He, Xu He, Yingxue Zhang, Ruiming Tang, Chen Ma:
Dynamically Expandable Graph Convolution for Streaming Recommendation. CoRR abs/2303.11700 (2023) - [i79]Yuening Wang, Yingxue Zhang, Antonios Valkanas, Ruiming Tang, Chen Ma, Jianye Hao, Mark Coates:
Structure Aware Incremental Learning with Personalized Imitation Weights for Recommender Systems. CoRR abs/2305.01204 (2023) - [i78]Xiangyang Li, Bo Chen, Lu Hou, Ruiming Tang:
CTRL: Connect Tabular and Language Model for CTR Prediction. CoRR abs/2306.02841 (2023) - [i77]Xianyu Chen, Jian Shen, Wei Xia, Jiarui Jin, Yakun Song, Weinan Zhang, Weiwen Liu, Menghui Zhu, Ruiming Tang, Kai Dong, Dingyin Xia, Yong Yu:
Set-to-Sequence Ranking-based Concept-aware Learning Path Recommendation. CoRR abs/2306.04234 (2023) - [i76]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) - [i75]Jieming Zhu, Guohao Cai, Junjie Huang, Zhenhua Dong, Ruiming Tang, Weinan Zhang:
ReLoop2: Building Self-Adaptive Recommendation Models via Responsive Error Compensation Loop. CoRR abs/2306.08808 (2023) - [i74]Yunjia Xi, Weiwen Liu, Jianghao Lin, Jieming Zhu, Bo Chen, Ruiming Tang, Weinan Zhang, Rui Zhang, Yong Yu:
Towards Open-World Recommendation with Knowledge Augmentation from Large Language Models. CoRR abs/2306.10933 (2023) - [i73]Chuhan Wu, Jingjie Li, Qinglin Jia, Hong Zhu, Yuan Fang, Ruiming Tang:
Contrastive Multi-view Framework for Customer Lifetime Value Prediction. CoRR abs/2306.14400 (2023) - [i72]Jianghao Lin, Yanru Qu, Wei Guo, Xinyi Dai, Ruiming Tang, Yong Yu, Weinan Zhang:
MAP: A Model-agnostic Pretraining Framework for Click-through Rate Prediction. CoRR abs/2308.01737 (2023) - [i71]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) - [i70]Bowei He, Xu He, Renrui Zhang, Yingxue Zhang, Ruiming Tang, Chen Ma:
Dynamic Embedding Size Search with Minimum Regret for Streaming Recommender System. CoRR abs/2308.07760 (2023) - [i69]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) - [i68]Jianghao Lin, Rong Shan, Chenxu Zhu, Kounianhua Du, Bo Chen, Shigang Quan, Ruiming Tang, Yong Yu, Weinan Zhang:
ReLLa: Retrieval-enhanced Large Language Models for Lifelong Sequential Behavior Comprehension in Recommendation. CoRR abs/2308.11131 (2023) - [i67]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) - [i66]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) - [i65]Qidong Liu, Fan Yan, Xiangyu Zhao, Zhaocheng Du, Huifeng Guo, Ruiming Tang, Feng Tian:
Diffusion Augmentation for Sequential Recommendation. CoRR abs/2309.12858 (2023) - [i64]Zhenhua Dong, Jieming Zhu, Weiwen Liu, Ruiming Tang:
Ten Challenges in Industrial Recommender Systems. CoRR abs/2310.04804 (2023) - [i63]Hangyu Wang, Ting Long, Liang Yin, Weinan Zhang, Wei Xia, Qichen Hong, Dingyin Xia, Ruiming Tang, Yong Yu:
GMOCAT: A Graph-Enhanced Multi-Objective Method for Computerized Adaptive Testing. CoRR abs/2310.07477 (2023) - [i62]Jianghao Lin, Bo Chen, Hangyu Wang, Yunjia Xi, Yanru Qu, Xinyi Dai, Kangning Zhang, Ruiming Tang, Yong Yu, Weinan Zhang:
ClickPrompt: CTR Models are Strong Prompt Generators for Adapting Language Models to CTR Prediction. CoRR abs/2310.09234 (2023) - [i61]Hao Wang, Zhichao Chen, Jiajun Fan, Haoxuan Li, Tianqiao Liu, Weiming Liu, Quanyu Dai, Yichao Wang, Zhenhua Dong, Ruiming Tang:
Optimal Transport for Treatment Effect Estimation. CoRR abs/2310.18286 (2023) - [i60]Hangyu Wang, Jianghao Lin, Xiangyang Li, Bo Chen, Chenxu Zhu, Ruiming Tang, Weinan Zhang, Yong Yu:
ALT: Towards Fine-grained Alignment between Language and CTR Models for Click-Through Rate Prediction. CoRR abs/2310.19453 (2023) - [i59]Mingjia Yin, Hao Wang, Xiang Xu, Likang Wu, Sirui Zhao, Wei Guo, Yong Liu, Ruiming Tang, Defu Lian, Enhong Chen:
APGL4SR: A Generic Framework with Adaptive and Personalized Global Collaborative Information in Sequential Recommendation. CoRR abs/2311.02816 (2023) - [i58]Fuyuan Lyu, Yaochen Hu, Xing Tang, Yingxue Zhang, Ruiming Tang, Xue Liu:
Towards Automated Negative Sampling in Implicit Recommendation. CoRR abs/2311.03526 (2023) - 2022
- [j9]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) - [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) - [j7]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) - [c84]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 - [c83]Haolun Wu, Chen Ma, Yingxue Zhang, Xue Liu, Ruiming Tang, Mark Coates:
Adapting Triplet Importance of Implicit Feedback for Personalized Recommendation. CIKM 2022: 2148-2157 - [c82]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 - [c81]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 - [c80]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 - [c79]Quanyu Dai, Yalei Lv, Jieming Zhu, Junjie Ye, Zhenhua Dong, Rui Zhang, Shu-Tao Xia, Ruiming Tang:
LCD: Adaptive Label Correction for Denoising Music Recommendation. CIKM 2022: 3903-3907 - [c78]Wei Xia, Weiwen Liu, Yifan Liu, Ruiming Tang:
Balancing Utility and Exposure Fairness for Integrated Ranking with Reinforcement Learning. CIKM 2022: 4590-4594 - [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]Fengyi Song, Bo Chen, Xiangyu Zhao, Huifeng Guo, Ruiming Tang:
AutoAssign: Automatic Shared Embedding Assignment in Streaming Recommendation. ICDM 2022: 458-467 - [c74]Weiwen Liu, Yunjia Xi, Jiarui Qin, Fei Sun, Bo Chen, Weinan Zhang, Rui Zhang, Ruiming Tang:
Neural Re-ranking in Multi-stage Recommender Systems: A Review. IJCAI 2022: 5512-5520 - [c73]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 - [c72]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 - [c71]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 - [c70]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 - [c69]Roberto Corizzo, Junfeng Ge, Colin Bellinger, Xiaoqiang Zhu, Paula Branco, Kuang-chih Lee, Nathalie Japkowicz, Ruiming Tang, Tao Zhuang, Han Zhu, Biye Jiang, Jiaxin Mao, Weinan Zhang:
4th Workshop on Deep Learning Practice and Theory for High-Dimensional Sparse and Imbalanced Data with KDD 2022. KDD 2022: 4860-4861 - [c68]Weiwen Liu, Jiarui Qin, Ruiming Tang, Bo Chen:
Neural Re-ranking for Multi-stage Recommender Systems. RecSys 2022: 698-699 - [c67]Jiarui Qin, Jiachen Zhu, Bo Chen, Zhirong Liu, Weiwen Liu, Ruiming Tang, Rui Zhang, Yong Yu, Weinan Zhang:
RankFlow: Joint Optimization of Multi-Stage Cascade Ranking Systems as Flows. SIGIR 2022: 814-824 - [c66]Yunjia Xi, Weiwen Liu, Jieming Zhu, Xilong Zhao, Xinyi Dai, Ruiming Tang, Weinan Zhang, Rui Zhang, Yong Yu:
Multi-Level Interaction Reranking with User Behavior History. SIGIR 2022: 1336-1346 - [c65]Enming Yuan, Wei Guo, Zhicheng He, Huifeng Guo, Chengkai Liu, Ruiming Tang:
Multi-Behavior Sequential Transformer Recommender. SIGIR 2022: 1642-1652 - [c64]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 - [c63]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 - [c62]Lu Wang, Ruiming Tang, Xiaofeng He, Xiuqiang He:
Hierarchical Imitation Learning via Subgoal Representation Learning for Dynamic Treatment Recommendation. WSDM 2022: 1081-1089 - [c61]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 - [c60]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 - [c59]Qi Wan, Xiangnan He, Xiang Wang, Jiancan Wu, Wei Guo, Ruiming Tang:
Cross Pairwise Ranking for Unbiased Item Recommendation. WWW 2022: 2370-2378 - [i57]Weijun Hong, Guilin Li, Weinan Zhang, Ruiming Tang, Yunhe Wang, Zhenguo Li, Yong Yu:
DropNAS: Grouped Operation Dropout for Differentiable Architecture Search. CoRR abs/2201.11679 (2022) - [i56]Weiwen Liu, Yunjia Xi, Jiarui Qin, Fei Sun, Bo Chen, Weinan Zhang, Rui Zhang, Ruiming Tang:
Neural Re-ranking in Multi-stage Recommender Systems: A Review. CoRR abs/2202.06602 (2022) - [i55]