Ruiming Tang

发表

Yunming Ye, Zhenguo Li, Huifeng Guo, 2017, DASFAA.

A Novel KNN Approach for Session-Based Recommendation

Feng Liu, Yunming Ye, Huifeng Guo, 2019, PAKDD.

Collaborative Filtering with Graph-Based Implicit Feedback

Yong Yu, Weinan Zhang, Ruiming Tang, 2017, 2017 International Conference on Computer Technology, Electronics and Communication (ICCTEC).

Item Tagging for Information Retrieval: A Tripartite Graph Neural Network based Approach

Jieming Zhu, Xi Xiao, Ruiming Tang, 2020, SIGIR.

Sampling-Based XML Data Pricing

Stéphane Bressan, Pierre Senellart, Antoine Amarilli, 2014 .

Large-scale Interactive Recommendation with Tree-structured Policy Gradient pdf

Yong Yu, Weinan Zhang, Han Cai, 2018, AAAI.

Edit Distance between XML and Probabilistic XML Documents

Stéphane Bressan, Huayu Wu, Ruiming Tang, 2011, DEXA.

Feature Generation by Convolutional Neural Network for Click-Through Rate Prediction

Bin Liu, Huifeng Guo, Ruiming Tang, 2019, WWW.

Novel Approaches to Accelerating the Convergence Rate of Markov Decision Process for Search Result Diversification

Feng Liu, Yunming Ye, Xutao Li, 2018, DASFAA.

DeepFM: An End-to-End Wide & Deep Learning Framework for CTR Prediction pdf

Yunming Ye, Zhenguo Li, Huifeng Guo, 2018, ArXiv.

A Framework for Conditioning Uncertain Relational Data

Stéphane Bressan, Huayu Wu, Reynold Cheng, 2012, DEXA.

Dual-attentional Factorization-Machines based Neural Network for User Response Prediction

Yunming Ye, Wei Guo, Feng Liu, 2020, WWW.

Interactive Recommender System via Knowledge Graph-enhanced Reinforcement Learning

Weinan Zhang, Xinyi Dai, Ruiming Tang, 2020, SIGIR.

Balancing Between Accuracy and Fairness for Interactive Recommendation with Reinforcement Learning

Feng Liu, Pheng-Ann Heng, Weiwen Liu, 2020, PAKDD.

Multi-graph Convolution Collaborative Filtering

Mark Coates, Chen Ma, Huifeng Guo, 2019, 2019 IEEE International Conference on Data Mining (ICDM).

What You Pay for Is What You Get

Stéphane Bressan, Patrick Valduriez, Dongxu Shao, 2013, DEXA.

A Framework for Sampling-Based XML Data Pricing

Stéphane Bressan, Pierre Senellart, Antoine Amarilli, 2016, Trans. Large Scale Data Knowl. Centered Syst..

PAL: a position-bias aware learning framework for CTR prediction in live recommender systems

Huifeng Guo, Ruiming Tang, Qing Liu, 2019, RecSys.

State representation modeling for deep reinforcement learning based recommendation

Yunming Ye, Weinan Zhang, Xutao Li, 2020, Knowl. Based Syst..

On efficient conditioning of probabilistic relational databases

Hong Zhu, Caicai Zhang, Ruiming Tang, 2016, Knowl. Based Syst..

An Efficient Conditioning Method for Probabilistic Relational Databases

Hong Zhu, Caicai Zhang, Ruiming Tang, 2014, WAIM.

A Practical Incremental Method to Train Deep CTR Models pdf

Yichao Wang, Huifeng Guo, Ruiming Tang, 2020, ArXiv.

U-rank: Utility-oriented Learning to Rank with Implicit Feedback

Weinan Zhang, Jun Wang, Xinyi Dai, 2020, CIKM.

An Adjustable Heat Conduction based KNN Approach for Session-based Recommendation pdf

Feng Liu, Yunming Ye, Huifeng Guo, 2018, ArXiv.

Order-aware Embedding Neural Network for CTR Prediction

Wei Guo, Wen Yang, Huifeng Guo, 2019, SIGIR.

The Price Is Right - Models and Algorithms for Pricing Data

Stéphane Bressan, Patrick Valduriez, Huayu Wu, 2013, DEXA.

2015 Ieee International Conference on Big Data (big Data) Mining Target Users for Online Marketing Based on App Store Data

Qiang Yang, Mingxuan Yuan, Ruiming Tang, 2022 .

Product-Based Neural Networks for User Response Prediction over Multi-Field Categorical Data

Yong Yu, Weinan Zhang, Huifeng Guo, 2018, ACM Trans. Inf. Syst..

Optimizing Ranking Algorithm in Recommender System via Deep Reinforcement Learning

Feng Liu, Ruiming Tang, Jianhua Han, 2019, 2019 International Conference on Artificial Intelligence and Advanced Manufacturing (AIAM).

Field-aware probabilistic embedding neural network for CTR prediction

Shengyu Zhang, Huifeng Guo, Ruiming Tang, 2018, RecSys.

Integration of Web Sources Under Uncertainty and Dependencies Using Probabilistic XML

Talel Abdessalem, Ruiming Tang, Mouhamadou Lamine Ba, 2014, DASFAA Workshops.

Conditioning Probabilistic Relational Data with Referential Constraints

Huayu Wu, Dongxu Shao, Ruiming Tang, 2014, DASFAA Workshops.

Get a Sample for a Discount - Sampling-Based XML Data Pricing

Stéphane Bressan, Pierre Senellart, Antoine Amarilli, 2014, DEXA.

Deep Reinforcement Learning based Recommendation with Explicit User-Item Interactions Modeling pdf

Feng Liu, Yunming Ye, Xutao Li, 2018, ArXiv.

An efficient and truthful pricing mechanism for team formation in crowdsourcing markets

Stéphane Bressan, Qing Liu, Tie Luo, 2015, 2015 IEEE International Conference on Communications (ICC).

DeepFM: A Factorization-Machine based Neural Network for CTR Prediction

Yunming Ye, Zhenguo Li, Huifeng Guo, 2017, IJCAI.

Measuring XML Structured-ness with Entropy

Stéphane Bressan, Huayu Wu, Ruiming Tang, 2011, WAIM Workshops.

GraphSAIL: Graph Structure Aware Incremental Learning for Recommender Systems

Wei Guo, Mark Coates, Huifeng Guo, 2020, CIKM.

Personalized Re-ranking with Item Relationships for E-commerce

Weiwen Liu, Ruiming Tang, Xiuqiang He, 2020, CIKM.

Personalized Re-ranking for Improving Diversity in Live Recommender Systems pdf

Xiangyu Zhang, Zhirong Liu, Yichao Wang, 2020, ArXiv.

AutoFIS: Automatic Feature Interaction Selection in Factorization Models for Click-Through Rate Prediction

Bin Liu, Yong Yu, Weinan Zhang, 2020, KDD.

DropNAS: Grouped Operation Dropout for Differentiable Architecture Search

Weinan Zhang, Weijun Hong, Zhenguo Li, 2020, IJCAI.

Expressing and Processing Path-Centric XML Queries

Stéphane Bressan, Tok Wang Ling, Huayu Wu, 2015, DEXA.

Conditioning Probabilistic XML (Extended Version)

Stéphane Bressan, Pierre Senellart, Dongxu Shao, 2013 .

Querying Semi-structured Data with Mutual Exclusion

Tok Wang Ling, Huayu Wu, Ruiming Tang, 2013, DASFAA.

A Hybrid Approach for General XML Query Processing

Stéphane Bressan, Tok Wang Ling, Huayu Wu, 2012, DEXA.

End-to-End Deep Reinforcement Learning based Recommendation with Supervised Embedding

Yunming Ye, Feng Liu, Xutao Li, 2020, WSDM.

AutoFeature: Searching for Feature Interactions and Their Architectures for Click-through Rate Prediction

Zhenguo Li, Bin Liu, Ruiming Tang, 2020, CIKM.

Holistic Neural Network for CTR Prediction

Yunming Ye, Huifeng Guo, Ruiming Tang, 2017, WWW.

Valuating Queries for Data Trading in Modern Cities

Stéphane Bressan, Huayu Wu, Ruiming Tang, 2015, 2015 IEEE International Conference on Data Mining Workshop (ICDMW).

An Embedding Learning Framework for Numerical Features in CTR Prediction

Zhenguo Li, Huifeng Guo, Ruiming Tang, 2020, KDD.

Semi-deterministic and Contrastive Variational Graph Autoencoder for Recommendation

Chenghua Lin, Ruiming Tang, Yue Ding, 2021, CIKM.

QA4PRF: A Question Answering Based Framework for Pseudo Relevance Feedback

Ruiming Tang, Xiuqiang He, Handong Ma, 2021, IEEE Access.

Enhancing Explicit and Implicit Feature Interactions via Information Sharing for Parallel Deep CTR Models

Zhirong Liu, Ruiming Tang, Xiuqiang He, 2021, CIKM.

3rd International Workshop on Deep Learning Practice for High-Dimensional Sparse Data with KDD 2021

Qingyao Ai, Ruiming Tang, Xiaoqiang Zhu, 2021, KDD.

Balancing Accuracy and Fairness for Interactive Recommendation with Reinforcement Learning pdf

Guangyong Chen, Ruiming Tang, Pheng Ann Heng, 2021, ArXiv.

Learning to Build High-Fidelity and Robust Environment Models

Zhenguo Li, Ruiming Tang, Yimin Huang, 2021, ECML/PKDD.

Content Filtering Enriched GNN Framework for News Recommendation pdf

Ruiming Tang, Xiuqiang He, Dandan Lin, 2021, ArXiv.

Context-aware Reranking with Utility Maximization for Recommendation pdf

Ruiming Tang, Xiuqiang He, Weinan Zhang, 2021, ArXiv.

Dual Graph enhanced Embedding Neural Network for CTR Prediction

Zhirong Liu, Huifeng Guo, Ruiming Tang, 2021, KDD.

AutoFT: Automatic Fine-Tune for Parameters Transfer Learning in Click-Through Rate Prediction pdf

Zhirong Liu, Ruiming Tang, Xiuqiang He, 2021, ArXiv.

Towards Low-loss 1-bit Quantization of User-item Representations for Top-K Recommendation pdf

Irwin King, Ruiming Tang, Xiuqiang He, 2021, ArXiv.

AIM: Automatic Interaction Machine for Click-Through Rate Prediction pdf

Zhenguo Li, Ruiming Tang, Xiuqiang He, 2021, IEEE Transactions on Knowledge and Data Engineering.

A Graph-Enhanced Click Model for Web Search

Yong Yu, Jianye Hao, Ruiming Tang, 2021, SIGIR.

An Adversarial Imitation Click Model for Information Retrieval

Yong Yu, Jianye Hao, Ruiming Tang, 2021, WWW.

On Effective Scheduling of Model-based Reinforcement Learning pdf

Zhenguo Li, Ruiming Tang, Yimin Huang, 2021, ArXiv.

Retrieval & Interaction Machine for Tabular Data Prediction

Zhirong Liu, Ruiming Tang, Xiuqiang He, 2021, KDD.

Extracting Attentive Social Temporal Excitation for Sequential Recommendation

Xin Xin, Ruiming Tang, Yue Ding, 2021, CIKM.

MISS: Multi-Interest Self-Supervised Learning Framework for Click-Through Rate Prediction pdf

Ruiming Tang, Xiuqiang He, Bo Chen, 2021, ArXiv.

ScaleFreeCTR: MixCache-based Distributed Training System for CTR Models with Huge Embedding Table

Huifeng Guo, Ruiming Tang, Xiuqiang He, 2021, SIGIR.

Deep Learning for Click-Through Rate Estimation

Ruiming Tang, Xiuqiang He, Jiarui Qin, 2021, IJCAI.