Huifeng Guo

发表

OptEmbed: Learning Optimal Embedding Table for Click-through Rate Prediction

Ruiming Tang, Yingxue Zhang, Hong Zhu, 2022, International Conference on Information and Knowledge Management.

CausalInt: Causal Inspired Intervention for Multi-Scenario Recommendation

Ruiming Tang, Zhenhua Dong, Zhirong Liu, 2022, KDD.

Learning Binarized Graph Representations with Multi-faceted Quantization Reinforcement for Top-K Recommendation

Irwin King, Ruiming Tang, Chen Ma, 2022, KDD.

Multi-Behavior Sequential Transformer Recommender

Ruiming Tang, Enming Yuan, Wei Guo, 2022, SIGIR.

SP2509, a Selective Inhibitor of LSD1, Suppresses Retinoblastoma Growth by Downregulating β-catenin Signaling

Y. Sang, Caixia Xu, Xiantao Sun, 2022, Investigative ophthalmology & visual science.

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

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

An Effective Post-training Embedding Binarization Approach for Fast Online Top-K Passage Matching

Irwin King, Ruiming Tang, Yifei Zhang, 2022, AACL.

Memorize, Factorize, or be Naive: Learning Optimal Feature Interaction Methods for CTR Prediction

Rui Zhang, Ruiming Tang, Xiuqiang He, 2021, 2022 IEEE 38th International Conference on Data Engineering (ICDE).

AutoGroup: Automatic Feature Grouping for Modelling Explicit High-Order Feature Interactions in CTR Prediction

Stefanos Zafeiriou, Zhenguo Li, Huifeng Guo, 2020, SIGIR.

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

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

Multi-graph Convolution Collaborative Filtering

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

A Framework for Recommending Accurate and Diverse Items Using Bayesian Graph Convolutional Neural Networks

Dengcheng Zhang, Mark Coates, Huifeng Guo, 2020, KDD.

Multi-Task Deep Recommender Systems: A Survey

Ha T. Lam, Ruiming Tang, Xiang Zhao, 2023, ArXiv.

A Comprehensive Survey on Automated Machine Learning for Recommendations

Ruiming Tang, Yejing Wang, Wenqi Fan, 2022, ACM Transactions on Recommender Systems.

Automated Machine Learning for Deep Recommender Systems: A Survey

Xiangyu Zhao, Ruiming Tang, Yejing Wang, 2022, ArXiv.

Dual Graph enhanced Embedding Neural Network for CTR Prediction

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

DSKmeans: A new kmeans-type approach to discriminative subspace clustering

Yunming Ye, Xiaohui Huang, Yan Li, 2014, Knowl. Based Syst..

State representation modeling for deep reinforcement learning based recommendation

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

Adaptive Low-Precision Training for Embeddings in Click-Through Rate Prediction

Rui Zhang, Rui Li, Ruiming Tang, 2022, AAAI.

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

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

Neighbor Interaction Aware Graph Convolution Networks for Recommendation

Mark Coates, Huifeng Guo, Xiuqiang He, 2020, SIGIR.

GraphSAIL: Graph Structure Aware Incremental Learning for Recommender Systems

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

IntTower: The Next Generation of Two-Tower Model for Pre-Ranking System

Sujian Li, Ruiming Tang, Wei Guo, 2022, CIKM.

Deep Graph Convolutional Networks with Hybrid Normalization for Accurate and Diverse Recommendation

Wei Guo, Xiuqiang He, Yingxue Zhang, 2021 .

An Embedding Learning Framework for Numerical Features in CTR Prediction

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

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

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

AutoAssign: Automatic Shared Embedding Assignment in Streaming Recommendation

Ruiming Tang, Fengyi Song, Xiangyu Zhao, 2022, 2022 IEEE International Conference on Data Mining (ICDM).

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

Rui Zhang, Ruiming Tang, Wei Guo, 2021, 2022 IEEE 38th International Conference on Data Engineering (ICDE).

Numerical Feature Representation with Hybrid N-ary Encoding

Rui Zhang, Ruiming Tang, Wei Guo, 2022, CIKM.

A Practical Incremental Method to Train Deep CTR Models pdf

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

Unsupervised Learning Style Classification for Learning Path Generation in Online Education Platforms

Rui Zhang, Ruiming Tang, Huifeng Guo, 2022, KDD.

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

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

How Can Recommender Systems Benefit from Large Language Models: A Survey

Weinan Zhang, Ruiming Tang, Bo Chen, 2023, ACM Transactions on Information Systems.

M. Coates, Ruiming Tang, Wei Guo, 2020, Proceedings of the 29th ACM International Conference on Information & Knowledge Management.

Field-aware probabilistic embedding neural network for CTR prediction

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

AutoML for Deep Recommender Systems: Fundamentals and Advances

Ruiming Tang, Yejing Wang, Wenqi Fan, 2023, WSDM.

AutoDis: Automatic Discretization for Embedding Numerical Features in CTR Prediction pdf

Bo Chen, Zhenguo Li, Huifeng Guo, 2020, ArXiv.

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

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

Ruiming Tang, Q. Liu, Huifeng Guo, 2019, Proceedings of the 13th ACM Conference on Recommender Systems.

Order-aware Embedding Neural Network for CTR Prediction

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

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

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

Holistic Neural Network for CTR Prediction

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

Time-aligned Exposure-enhanced Model for Click-Through Rate Prediction

Jieming Zhu, Ruiming Tang, Wei Guo, 2023, ArXiv.

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

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

Single-shot Feature Selection for Multi-task Recommendations

Ruiming Tang, Yejing Wang, Zhenhua Dong, 2023, SIGIR.

AutoGen: An Automated Dynamic Model Generation Framework for Recommender System

Weinan Zhang, Ruiming Tang, Xiangyu Zhao, 2023, WSDM.

AutoTransfer: Instance Transfer for Cross-Domain Recommendations

Ruiming Tang, Xiangyu Zhao, Bo Chen, 2023, SIGIR.

PLATE: A Prompt-Enhanced Paradigm for Multi-Scenario Recommendations

Rui Zhang, Ruiming Tang, Xiangyu Zhao, 2023, SIGIR.

AutoHash: Learning Higher-Order Feature Interactions for Deep CTR Prediction

Bin Liu, Stefanos Zafeiriou, Jun Wang, 2022, IEEE Transactions on Knowledge and Data Engineering.

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

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

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

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

Scenario-Aware Hierarchical Dynamic Network for Multi-Scenario Recommendation

Ruiming Tang, Bo Chen, Yichao Wang, 2023, ArXiv.

BLM-Rank: A Bayesian Linear Method for Learning to Rank and Its GPU Implementation

Yunming Ye, Xutao Li, Huifeng Guo, 2016, IEICE Trans. Inf. Syst..

AutoAssign+: Automatic Shared Embedding Assignment in Streaming Recommendation

Ruiming Tang, Fengyi Song, Xiangyu Zhao, 2023, Knowledge and Information Systems.

OptEmbed: Learning Optimal Embedding Table for Click-through Rate Prediction

Ruiming Tang, Yingxue Zhang, Hong Zhu, 2022, CIKM.

Top-aware reinforcement learning based recommendation

Yunming Ye, Xutao Li, Huifeng Guo, 2020, Neurocomputing.

A Unified Framework for Multi-Domain CTR Prediction via Large Language Models

Huifeng Guo, Xiangyang Li, Xiangyu Zhao, 2023, ArXiv.

Hierarchical Projection Enhanced Multi-behavior Recommendation

Rui Zhang, Ruiming Tang, Wei Guo, 2023, KDD.

Compressed Interaction Graph based Framework for Multi-behavior Recommendation

Rui Zhang, Ruiming Tang, Enming Yuan, 2023, WWW.

B. Liu, S. Zafeiriou, Zhenguo Li, 2020, Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval.

Disentangling Past-Future Modeling in Sequential Recommendation via Dual Networks

Ruiming Tang, Enming Yuan, Wei Guo, 2022, CIKM.

Tired of Plugins? Large Language Models Can Be End-To-End Recommenders

Huifeng Guo, Xinyi Dai, Xiangyang Li, 2024, 2404.00702.

Diffusion Augmentation for Sequential Recommendation

Ruiming Tang, Huifeng Guo, Zhaochen Du, 2023, CIKM.

CausalInt: Causal Inspired Intervention for Multi-Scenario Recommendation

Ruiming Tang, Zhenhua Dong, Zhirong Liu, 2022, KDD.

HAMUR: Hyper Adapter for Multi-Domain Recommendation

Ruiming Tang, Bo Chen, Yichao Wang, 2023, CIKM.

Content Filtering Enriched GNN Framework for News Recommendation pdf

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

Disentangling Past-Future Modeling in Sequential Recommendation via Dual Networks

Ruiming Tang, Enming Yuan, Wei Guo, 2022, CIKM.