Yong Liu

According to our database, Yong Liu authored at least 129 papers between 2013 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

Conditional Potential User Mining framework via explainable surrogate models.

Yibowen Zhao, Yonghui Xu, Yong Liu, Luwei Yang, Wen Jiang, Wei Ning, Xiaofang Sun, Lizhen Cui

Expert Syst. Appl., 2025

2024

A Survey on Reinforcement Learning for Recommender Systems.

Yuanguo Lin, Yong Liu, Fan Lin, Lixin Zou, Pengcheng Wu, Wenhua Zeng, Huanhuan Chen, Chunyan Miao

IEEE Trans. Neural Networks Learn. Syst., October, 2024

Package Arrival Time Prediction via Knowledge Distillation Graph Neural Network.

Lei Zhang, Yong Liu, Zhiwei Zeng, Yiming Cao, Xingyu Wu, Yonghui Xu, Zhiqi Shen, Lizhen Cui

ACM Trans. Knowl. Discov. Data, June, 2024

Estimating package arrival time via heterogeneous hypergraph neural network.

Lei Zhang, Xingyu Wu, Yong Liu, Xin Zhou, Yiming Cao, Yonghui Xu, Lizhen Cui, Chunyan Miao

Expert Syst. Appl., March, 2024

Converse Attention Knowledge Transfer for Low-Resource Named Entity Recognition.

Shengfei Lyu, Linghao Sun, Huixiong Yi, Yong Liu, Huanhuan Chen, Chunyan Miao

Int. J. Crowd Sci., 2024

Enhancing CTR Prediction in Recommendation Domain with Search Query Representation.

Yuening Wang, Chen Ma, Yaochen Hu, Wei Guo, Yingxue Zhang, Huifeng Guo, Yong Liu, Mark Coates

CoRR, 2024

ToolACE: Winning the Points of LLM Function Calling.

Weiwen Liu, Xu Huang, Xingshan Zeng, Xinlong Hao, Shuai Yu, Dexun Li, Shuai Wang, Weinan Gan, Zhengying Liu, Yuanqing Yu, Zezhong Wang, Yuxian Wang, Wu Ning, Yutai Hou, Bin Wang, Chuhan Wu, Xinzhi Wang, Yong Liu, Yasheng Wang, Duyu Tang, Dandan Tu, Lifeng Shang, Xin Jiang, Ruiming Tang, Defu Lian, Qun Liu, Enhong Chen

CoRR, 2024

Denoising Pre-Training and Customized Prompt Learning for Efficient Multi-Behavior Sequential Recommendation.

Hao Wang, Yongqiang Han, Kefan Wang, Kai Cheng, Zhen Wang, Wei Guo, Yong Liu, Defu Lian, Enhong Chen

CoRR, 2024

All Roads Lead to Rome: Unveiling the Trajectory of Recommender Systems Across the LLM Era.

Bo Chen, Xinyi Dai, Huifeng Guo, Wei Guo, Weiwen Liu, Yong Liu, Jiarui Qin, Ruiming Tang, Yichao Wang, Chuhan Wu, Yaxiong Wu, Hao Zhang

CoRR, 2024

Entropy Law: The Story Behind Data Compression and LLM Performance.

Mingjia Yin, Chuhan Wu, Yufei Wang, Hao Wang, Wei Guo, Yasheng Wang, Yong Liu, Ruiming Tang, Defu Lian, Enhong Chen

CoRR, 2024

CoIR: A Comprehensive Benchmark for Code Information Retrieval Models.

Xiangyang Li, Kuicai Dong, Yi Quan Lee, Wei Xia, Yichun Yin, Hao Zhang, Yong Liu, Yasheng Wang, Ruiming Tang

CoRR, 2024

Evaluating the External and Parametric Knowledge Fusion of Large Language Models.

Hao Zhang, Yuyang Zhang, Xiaoguang Li, Wenxuan Shi, Haonan Xu, Huanshuo Liu, Yasheng Wang, Lifeng Shang, Qun Liu, Yong Liu, Ruiming Tang

CoRR, 2024

CtrlA: Adaptive Retrieval-Augmented Generation via Probe-Guided Control.

Huanshuo Liu, Hao Zhang, Zhijiang Guo, Kuicai Dong, Xiangyang Li, Yi Quan Lee, Cong Zhang, Yong Liu

CoRR, 2024

Meta-Task Planning for Language Agents.

Cong Zhang, Derrick-Goh-Xin Deik, Dexun Li, Hao Zhang, Yong Liu

CoRR, 2024

Learning Partially Aligned Item Representation for Cross-Domain Sequential Recommendation.

Mingjia Yin, Hao Wang, Wei Guo, Yong Liu, Zhi Li, Sirui Zhao, Defu Lian, Enhong Chen

CoRR, 2024

Multi-view Content-aware Indexing for Long Document Retrieval.

Kuicai Dong, Derrick-Goh-Xin Deik, Yi Quan Lee, Hao Zhang, Xiangyang Li, Cong Zhang, Yong Liu

CoRR, 2024

END4Rec: Efficient Noise-Decoupling for Multi-Behavior Sequential Recommendation.

Yongqiang Han, Hao Wang, Kefan Wang, Likang Wu, Zhi Li, Wei Guo, Yong Liu, Defu Lian, Enhong Chen

CoRR, 2024

Sparse MeZO: Less Parameters for Better Performance in Zeroth-Order LLM Fine-Tuning.

Yong Liu, Zirui Zhu, Chaoyu Gong, Minhao Cheng, Cho-Jui Hsieh, Yang You

CoRR, 2024

Aligning Crowd Feedback via Distributional Preference Reward Modeling.

Dexun Li, Cong Zhang, Kuicai Dong, Derrick-Goh-Xin Deik, Ruiming Tang, Yong Liu

CoRR, 2024

Helen: Optimizing CTR Prediction Models with Frequency-wise Hessian Eigenvalue Regularization.

Zirui Zhu, Yong Liu, Zangwei Zheng, Huifeng Guo, Yang You

Proceedings of the ACM on Web Conference 2024, 2024

The 2nd Workshop on Recommendation with Generative Models.

Wenjie Wang, Yang Zhang, Xinyu Lin, Fuli Feng, Weiwen Liu, Yong Liu, Xiangyu Zhao, Wayne Xin Zhao, Yang Song, Xiangnan He

Proceedings of the Companion Proceedings of the ACM on Web Conference 2024, 2024

Efficient Noise-Decoupling for Multi-Behavior Sequential Recommendation.

Yongqiang Han, Hao Wang, Kefan Wang, Likang Wu, Zhi Li, Wei Guo, Yong Liu, Defu Lian, Enhong Chen

Proceedings of the ACM on Web Conference 2024, 2024

User Behavior Enriched Temporal Knowledge Graphs for Sequential Recommendation.

Hengchang Hu, Wei Guo, Xu Liu, Yong Liu, Ruiming Tang, Rui Zhang, Min-Yen Kan

Proceedings of the 17th ACM International Conference on Web Search and Data Mining, 2024

Dataset Regeneration for Sequential Recommendation.

Mingjia Yin, Hao Wang, Wei Guo, Yong Liu, Suojuan Zhang, Sirui Zhao, Defu Lian, Enhong Chen

Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024

Parameter-Efficient Conversational Recommender System as a Language Processing Task.

Mathieu Ravaut, Hao Zhang, Lu Xu, Aixin Sun, Yong Liu

Proceedings of the 18th Conference of the European Chapter of the Association for Computational Linguistics, 2024

Enhancing Click-through Rate Prediction in Recommendation Domain with Search Query Representation.

Yuening Wang, Man Chen, Yaochen Hu, Wei Guo, Yingxue Zhang, Huifeng Guo, Yong Liu, Mark Coates

Proceedings of the 33rd ACM International Conference on Information and Knowledge Management, 2024

Beyond Prototypes: Semantic Anchor Regularization for Better Representation Learning.

Yanqi Ge, Qiang Nie, Ye Huang, Yong Liu, Chengjie Wang, Feng Zheng, Wen Li, Lixin Duan

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

Multicomponent Adversarial Domain Adaptation: A General Framework.

Chang'an Yi, Haotian Chen, Yonghui Xu, Huanhuan Chen, Yong Liu, Haishu Tan, Yuguang Yan, Han Yu

IEEE Trans. Neural Networks Learn. Syst., October, 2023

Aspect-Guided Syntax Graph Learning for Explainable Recommendation.

Yidan Hu, Yong Liu, Chunyan Miao, Gongqi Lin, Yuan Miao

IEEE Trans. Knowl. Data Eng., August, 2023

Dynamic Multi-Objective Optimization Framework With Interactive Evolution for Sequential Recommendation.

Wei Zhou, Yong Liu, Min Li, Yu Wang, Zhiqi Shen, Liang Feng, Zexuan Zhu

IEEE Trans. Emerg. Top. Comput. Intell., August, 2023

SelfCF: A Simple Framework for Self-supervised Collaborative Filtering.

Xin Zhou, Aixin Sun, Yong Liu, Jie Zhang, Chunyan Miao

Trans. Recomm. Syst., June, 2023

Learning Hierarchical Review Graph Representations for Recommendation.

Yong Liu, Susen Yang, Yinan Zhang, Chunyan Miao, Zaiqing Nie, Juyong Zhang

IEEE Trans. Knowl. Data Eng., 2023

Contextualized Graph Attention Network for Recommendation With Item Knowledge Graph.

Yong Liu, Susen Yang, Yonghui Xu, Chunyan Miao, Min Wu, Juyong Zhang

IEEE Trans. Knowl. Data Eng., 2023

Neighbor-Anchoring Adversarial Graph Neural Networks.

Zemin Liu, Yuan Fang, Yong Liu, Vincent W. Zheng

IEEE Trans. Knowl. Data Eng., 2023

Multi-Modality Image Fusion and Object Detection Based on Semantic Information.

Yong Liu, Xin Zhou, Wei Zhong

Entropy, 2023

Unsupervised Representation Learning for Time Series: A Review.

Qianwen Meng, Hangwei Qian, Yong Liu, Yonghui Xu, Zhiqi Shen, Lizhen Cui

CoRR, 2023

A Survey on Federated Recommendation Systems.

Zehua Sun, Yonghui Xu, Yong Liu, Wei He, Yali Jiang, Fangzhao Wu, Lizhen Cui

CoRR, 2023

KR4SL: knowledge graph reasoning for explainable prediction of synthetic lethality.

Ke Zhang, Min Wu, Yong Liu, Yimiao Feng, Jie Zheng

Bioinform., 2023

Bootstrap Latent Representations for Multi-modal Recommendation.

Xin Zhou, Hongyu Zhou, Yong Liu, Zhiwei Zeng, Chunyan Miao, Pengwei Wang, Yuan You, Feijun Jiang

Proceedings of the ACM Web Conference 2023, 2023

Inductive Graph Transformer for Delivery Time Estimation.

Xin Zhou, Jinglong Wang, Yong Liu, Xingyu Wu, Zhiqi Shen, Cyril Leung

Proceedings of the Sixteenth ACM International Conference on Web Search and Data Mining, 2023

AutoML for Deep Recommender Systems: Fundamentals and Advances.

Ruiming Tang, Bo Chen, Yejing Wang, Huifeng Guo, Yong Liu, Wenqi Fan, Xiangyu Zhao

Proceedings of the Sixteenth ACM International Conference on Web Search and Data Mining, 2023

WSDM 2023 Workshop on Interactive Recommender Systems.

Yong Liu, Hao Zhang, Zhu Sun, Shoujin Wang, Jie Zhang

Proceedings of the Sixteenth ACM International Conference on Web Search and Data Mining, 2023

User Behavior Modeling with Deep Learning for Recommendation: Recent Advances.

Weiwen Liu, Wei Guo, Yong Liu, Ruiming Tang, Hao Wang

Proceedings of the 17th ACM Conference on Recommender Systems, 2023

RecSys Challenge 2023: Deep Funnel Optimization with a Focus on User Privacy.

Rahul Agrawal, Sarang Brahme, Sourav Maitra, Saikishore Kalloori, Abhishek Srivastava, Yong Liu, Athirai A. Irissappane

Proceedings of the 17th ACM Conference on Recommender Systems, 2023

RecSys Challenge 2023 Dataset: Ads Recommendations in Online Advertising.

Rahul Agrawal, Sarang Brahme, Sourav Maitra, Abhishek Srivastava, Athirai A. Irissappane, Yong Liu, Saikishore Kalloori

Proceedings of the ACM RecSys Challenge 2023, Singapore, 19 September 2023, 2023

Layer-refined Graph Convolutional Networks for Recommendation.

Xin Zhou, Donghui Lin, Yong Liu, Chunyan Miao

Proceedings of the 39th IEEE International Conference on Data Engineering, 2023

Delivery Time Prediction Using Large-Scale Graph Structure Learning Based on Quantile Regression.

Lei Zhang, Xin Zhou, Zhiwei Zeng, Yiming Cao, Yonghui Xu, Mingliang Wang, Xingyu Wu, Yong Liu, Lizhen Cui, Zhiqi Shen

Proceedings of the 39th IEEE International Conference on Data Engineering, 2023

Cross-Domain Disentangled Learning for E-Commerce Live Streaming Recommendation.

Yixin Zhang, Yong Liu, Hao Xiong, Yi Liu, Fuqiang Yu, Wei He, Yonghui Xu, Lizhen Cui, Chunyan Miao

Proceedings of the 39th IEEE International Conference on Data Engineering, 2023

APGL4SR: A Generic Framework with Adaptive and Personalized Global Collaborative Information in Sequential Recommendation.

Mingjia Yin, Hao Wang, Xiang Xu, Likang Wu, Sirui Zhao, Wei Guo, Yong Liu, Ruiming Tang, Defu Lian, Enhong Chen

Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023

The 1st Workshop on Recommendation with Generative Models.

Wenjie Wang, Yong Liu, Yang Zhang, Weiwen Liu, Fuli Feng, Xiangnan He, Aixin Sun

Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023

Adaptive Multi-Modalities Fusion in Sequential Recommendation Systems.

Hengchang Hu, Wei Guo, Yong Liu, Min-Yen Kan

Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023

DFFM: Domain Facilitated Feature Modeling for CTR Prediction.

Wei Guo, Chenxu Zhu, Fan Yan, Bo Chen, Weiwen Liu, Huifeng Guo, Hongkun Zheng, Yong Liu, Ruiming Tang

Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023

Next POI Recommendation with Dynamic Graph and Explicit Dependency.

Feiyu Yin, Yong Liu, Zhiqi Shen, Lisi Chen, Shuo Shang, Peng Han

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

Revisiting Item Promotion in GNN-Based Collaborative Filtering: A Masked Targeted Topological Attack Perspective.

Yongwei Wang, Yong Liu, Zhiqi Shen

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

MHCCL: Masked Hierarchical Cluster-Wise Contrastive Learning for Multivariate Time Series.

Qianwen Meng, Hangwei Qian, Yong Liu, Lizhen Cui, Yonghui Xu, Zhiqi Shen

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

Evolutionary Search With Multiview Prediction for Dynamic Multiobjective Optimization.

Wei Zhou, Liang Feng, Kay Chen Tan, Min Jiang, Yong Liu

IEEE Trans. Evol. Comput., 2022

ATPL: Mutually enhanced adversarial training and pseudo labeling for unsupervised domain adaptation.

Chang'an Yi, Haotian Chen, Yonghui Xu, Yong Liu, Lei Jiang, Haishu Tan

Knowl. Based Syst., 2022

Hierarchical reinforcement learning with dynamic recurrent mechanism for course recommendation.

Yuanguo Lin, Fan Lin, Wenhua Zeng, Jianbing Xiahou, Li Li, Pengcheng Wu, Yong Liu, Chunyan Miao

Knowl. Based Syst., 2022

Federated low-rank tensor projections for sequential recommendation.

Li Li, Fan Lin, Jianbing Xiahou, Yuanguo Lin, Pengcheng Wu, Yong Liu

Knowl. Based Syst., 2022

Minimalist and High-performance Conversational Recommendation with Uncertainty Estimation for User Preference.

Yinan Zhang, Boyang Li, Yong Liu, You Yuan, Chunyan Miao

CoRR, 2022

Pre-training graph neural networks for link prediction in biomedical networks.

Yahui Long, Min Wu, Yong Liu, Yuan Fang, Chee Keong Kwoh, Jinmiao Chen, Jiawei Luo, Xiaoli Li

Bioinform., 2022

Self-Supervised Reinforcement Learning with dual-reward for knowledge-aware recommendation.

Wei Zhang, Yuanguo Lin, Yong Liu, Huanyu You, Pengcheng Wu, Fan Lin, Xiuze Zhou

Appl. Soft Comput., 2022

Context-aware reinforcement learning for course recommendation.

Yuanguo Lin, Fan Lin, Lvqing Yang, Wenhua Zeng, Yong Liu, Pengcheng Wu

Appl. Soft Comput., 2022

Heterogeneous star graph attention network for product attributes prediction.

Xuejiao Zhao, Yong Liu, Yonghui Xu, Yonghua Yang, Xusheng Luo, Chunyan Miao

Adv. Eng. Informatics, 2022

Random Sharpness-Aware Minimization.

Yong Liu, Siqi Mai, Minhao Cheng, Xiangning Chen, Cho-Jui Hsieh, Yang You

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Graph-Flashback Network for Next Location Recommendation.

Xuan Rao, Lisi Chen, Yong Liu, Shuo Shang, Bin Yao, Peng Han

Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

Enhancing Sequential Recommendation with Graph Contrastive Learning.

Yixin Zhang, Yong Liu, Yonghui Xu, Hao Xiong, Chenyi Lei, Wei He, Lizhen Cui, Chunyan Miao

Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022

Concurrent Adversarial Learning for Large-Batch Training.

Yong Liu, Xiangning Chen, Minhao Cheng, Cho-Jui Hsieh, Yang You

Proceedings of the Tenth International Conference on Learning Representations, 2022

Neighbor-Anchoring Adversarial Graph Neural Networks (Extended Abstract).

Zemin Liu, Yuan Fang, Yong Liu, Vincent W. Zheng

Proceedings of the 38th IEEE International Conference on Data Engineering, 2022

Joint Evidential $K$-Nearest Neighbor Classification.

Chaoyu Gong, Yongbin Li, Yong Liu, Pei-hong Wang, Yang You

Proceedings of the 38th IEEE International Conference on Data Engineering, 2022

Self-reconstructive evidential clustering for high-dimensional data.

Chaoyu Gong, Yongbin Liu, Di Fu, Yong Liu, Pei-hong Wang, Yang You

Proceedings of the 38th IEEE International Conference on Data Engineering, 2022

History-Aware Hierarchical Transformer for Multi-session Open-domain Dialogue System.

Tong Zhang, Yong Liu, Boyang Li, Zhiwei Zeng, Pengwei Wang, Yuan You, Chunyan Miao, Lizhen Cui

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2022, 2022

SAER: Sentiment-Opinion Alignment Explainable Recommendation.

Xiaoning Zong, Yong Liu, Yonghui Xu, Yixin Zhang, Zhiqi Shen, Yonghua Yang, Lizhen Cui

Proceedings of the Database Systems for Advanced Applications, 2022

Diffusion-Based Graph Contrastive Learning for Recommendation with Implicit Feedback.

Lingzi Zhang, Yong Liu, Xin Zhou, Chunyan Miao, Guoxin Wang, Haihong Tang

Proceedings of the Database Systems for Advanced Applications, 2022

Towards Efficient and Scalable Sharpness-Aware Minimization.

Yong Liu, Siqi Mai, Xiangning Chen, Cho-Jui Hsieh, Yang You

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

Memory Bank Augmented Long-tail Sequential Recommendation.

Yidan Hu, Yong Liu, Chunyan Miao, Yuan Miao

Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022

Toward Knowledge-Enriched Conversational Recommendation Systems.

Tong Zhang, Yong Liu, Boyang Li, Peixiang Zhong, Chen Zhang, Hao Wang, Chunyan Miao

Proceedings of the 4th Workshop on NLP for Conversational AI, 2022

Go Wider Instead of Deeper.

Fuzhao Xue, Ziji Shi, Futao Wei, Yuxuan Lou, Yong Liu, Yang You

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021

Remote Heart Rate Measurement From Near-Infrared Videos Based on Joint Blind Source Separation With Delay-Coordinate Transformation.

Juan Cheng, Ping Wang, Rencheng Song, Yu Liu, Chang Li, Yong Liu, Xun Chen

IEEE Trans. Instrum. Meas., 2021

Adaptive Power Iteration Clustering.

Bo Liu, Yong Liu, Huiyan Zhang, Yonghui Xu, Can Tang, Lianggui Tang, Huafeng Qin, Chunyan Miao

Knowl. Based Syst., 2021

Adaptive course recommendation in MOOCs.

Yuanguo Lin, Shibo Feng, Fan Lin, Wenhua Zeng, Yong Liu, Pengcheng Wu

Knowl. Based Syst., 2021

Hierarchical Aspect-guided Explanation Generation for Explainable Recommendation.

Yidan Hu, Yong Liu, Chunyan Miao, Gongqi Lin, Yuan Miao

CoRR, 2021

Geometry-Entangled Visual Semantic Transformer for Image Captioning.

Ling Cheng, Wei Wei, Feida Zhu, Yong Liu, Chunyan Miao

CoRR, 2021

A Survey on Reinforcement Learning for Recommender Systems.

Yuanguo Lin, Yong Liu, Fan Lin, Pengcheng Wu, Wenhua Zeng, Chunyan Miao

CoRR, 2021

KECRS: Towards Knowledge-Enriched Conversational Recommendation System.

Tong Zhang, Yong Liu, Peixiang Zhong, Chen Zhang, Hao Wang, Chunyan Miao

CoRR, 2021

KG4SL: knowledge graph neural network for synthetic lethality prediction in human cancers.

Shike Wang, Fan Xu, Yunyang Li, Jie Wang, Ke Zhang, Yong Liu, Min Wu, Jie Zheng

Bioinform., 2021

Graph contextualized attention network for predicting synthetic lethality in human cancers.

Yahui Long, Min Wu, Yong Liu, Jie Zheng, Chee Keong Kwoh, Jiawei Luo, Xiaoli Li

Bioinform., 2021

Pre-training Graph Transformer with Multimodal Side Information for Recommendation.

Yong Liu, Susen Yang, Chenyi Lei, Guoxin Wang, Haihong Tang, Juyong Zhang, Aixin Sun, Chunyan Miao

Proceedings of the MM '21: ACM Multimedia Conference, Virtual Event, China, October 20, 2021

Understanding Chinese Video and Language via Contrastive Multimodal Pre-Training.

Chenyi Lei, Shixian Luo, Yong Liu, Wanggui He, Jiamang Wang, Guoxin Wang, Haihong Tang, Chunyan Miao, Houqiang Li

Proceedings of the MM '21: ACM Multimedia Conference, Virtual Event, China, October 20, 2021

Initialization Matters: Regularizing Manifold-informed Initialization for Neural Recommendation Systems.

Yinan Zhang, Boyang Li, Yong Liu, Hao Wang, Chunyan Miao

Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

SEMI: A Sequential Multi-Modal Information Transfer Network for E-Commerce Micro-Video Recommendations.

Chenyi Lei, Yong Liu, Lingzi Zhang, Guoxin Wang, Haihong Tang, Houqiang Li, Chunyan Miao

Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

Diversity-Promoting Deep Reinforcement Learning for Interactive Recommendation.

Yong Liu, Zhiqi Shen, Yinan Zhang, Lizhen Cui

Proceedings of the ICCSE '21: 5th International Conference on Crowd Science and Engineering, Jinan, China, October 16, 2021

The Skyline of Counterfactual Explanations for Machine Learning Decision Models.

Yongjie Wang, Qinxu Ding, Ke Wang, Yue Liu, Xingyu Wu, Jinglong Wang, Yong Liu, Chunyan Miao

Proceedings of the CIKM '21: The 30th ACM International Conference on Information and Knowledge Management, Virtual Event, Queensland, Australia, November 1, 2021

Unsupervised Categorical Representation Learning for Package Arrival Time Prediction.

Yang Li, Xingyu Wu, Jinglong Wang, Yong Liu, Xiaoqing Wang, Yuming Deng, Chunyan Miao

Proceedings of the CIKM '21: The 30th ACM International Conference on Information and Knowledge Management, Virtual Event, Queensland, Australia, November 1, 2021

Keyword-Guided Neural Conversational Model.

Peixiang Zhong, Yong Liu, Hao Wang, Chunyan Miao

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

A Hybrid Bandit Framework for Diversified Recommendation.

Qinxu Ding, Yong Liu, Chunyan Miao, Fei Cheng, Haihong Tang

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

Classification of Travel Patterns Including Wandering Based on Bi-directional Long Short-Term Memory Networks.

Nhu Khue Vuong, Yong Liu, Syin Chan, Chiew Tong Lau, Zhenghua Chen, Min Wu, Xiaoli Li

Proceedings of the Generalization with Deep Learning: For Improvement on Sensing Capability, 2021

2020

SL²MF: Predicting Synthetic Lethality in Human Cancers via Logistic Matrix Factorization.

Yong Liu, Min Wu, Chenghao Liu, Xiaoli Li, Jie Zheng

IEEE ACM Trans. Comput. Biol. Bioinform., 2020

Spectral-Spatial Exploration for Hyperspectral Image Classification via the Fusion of Fully Convolutional Networks.

Liang Zou, Xingliang Zhu, Changfeng Wu, Yong Liu, Lei Qu

IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2020

Kernel-target alignment based non-linear metric learning.

Yonghui Xu, Chunyan Miao, Yong Liu, Hengjie Song, Yi Hu, Huaqing Min

Neurocomputing, 2020

A Pre-training Strategy for Recommendation.

Susen Yang, Yong Liu, Chenyi Lei, Guoxin Wang, Haihong Tang, Juyong Zhang, Chunyan Miao

CoRR, 2020

Endowing Empathetic Dialogue Systems with Personas.

Peixiang Zhong, Yan Sun, Yong Liu, Chen Zhang, Hao Wang, Zaiqing Nie, Chunyan Miao

CoRR, 2020

Learning Hierarchical Review Graph Representation for Recommendation.

Susen Yang, Yong Liu, Yinan Zhang, Chunyan Miao, Zaiqing Nie, Juyong Zhang

CoRR, 2020

Stack-VS: Stacked Visual-Semantic Attention for Image Caption Generation.

Ling Cheng, Wei Wei, Xianling Mao, Yong Liu, Chunyan Miao

IEEE Access, 2020

Learning Personalized Itemset Mapping for Cross-Domain Recommendation.

Yinan Zhang, Yong Liu, Peng Han, Chunyan Miao, Lizhen Cui, Baoli Li, Haihong Tang

Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020

Contextualized Point-of-Interest Recommendation.

Peng Han, Zhongxiao Li, Yong Liu, Peilin Zhao, Jing Li, Hao Wang, Shuo Shang

Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020

Towards Persona-Based Empathetic Conversational Models.

Peixiang Zhong, Chen Zhang, Hao Wang, Yong Liu, Chunyan Miao

Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, 2020

Deep learning with long short-term memory networks for classification of dementia related travel patterns.

Nhu Khue Vuong, Yong Liu, Syin Chan, Chiew Tong Lau, Zhenghua Chen, Min Wu, Xiaoli Li

Proceedings of the 42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society, 2020

Diversified Interactive Recommendation with Implicit Feedback.

Yong Liu, Yingtai Xiao, Qiong Wu, Chunyan Miao, Juyong Zhang, Binqiang Zhao, Haihong Tang

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019

Bandit Learning for Diversified Interactive Recommendation.

Yong Liu, Yingtai Xiao, Qiong Wu, Chunyan Miao, Juyong Zhang

CoRR, 2019

Recent Advances in Diversified Recommendation.

Qiong Wu, Yong Liu, Chunyan Miao, Yin Zhao, Lu Guan, Haihong Tang

CoRR, 2019

Diversity-Promoting Deep Reinforcement Learning for Interactive Recommendation.

Yong Liu, Yinan Zhang, Qiong Wu, Chunyan Miao, Lizhen Cui, Binqiang Zhao, Yin Zhao, Lu Guan

CoRR, 2019

Multi-Scale Quasi-RNN for Next Item Recommendation.

Chaoyue He, Yong Liu, Qingyu Guo, Chunyan Miao

CoRR, 2019

GCN-MF: Disease-Gene Association Identification By Graph Convolutional Networks and Matrix Factorization.

Peng Han, Peng Yang, Peilin Zhao, Shuo Shang, Yong Liu, Jiayu Zhou, Xin Gao, Panos Kalnis

Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2019

PD-GAN: Adversarial Learning for Personalized Diversity-Promoting Recommendation.

Qiong Wu, Yong Liu, Chunyan Miao, Binqiang Zhao, Yin Zhao, Lu Guan

Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

2018

Robust Cost-Sensitive Learning for Recommendation with Implicit Feedback.

Peng Yang, Peilin Zhao, Yong Liu, Xin Gao

Proceedings of the 2018 SIAM International Conference on Data Mining, 2018

Dynamic Bayesian Logistic Matrix Factorization for Recommendation with Implicit Feedback.

Yong Liu, Lifan Zhao, Guimei Liu, Xinyan Lu, Peng Gao, Xiao-Li Li, Zhihui Jin

Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018

2017

Learning User Dependencies for Recommendation.

Yong Liu, Peilin Zhao, Xin Liu, Min Wu, Lixin Duan, Xiaoli Li

Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017

Online Multitask Relative Similarity Learning.

Shuji Hao, Peilin Zhao, Yong Liu, Steven C. H. Hoi, Chunyan Miao

Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017

An Empirical Study on Collective Online Behaviors of Extremist Supporters.

Jung-Jae Kim, Yong Liu, Wee-Yong Lim, Vrizlynn L. L. Thing

Proceedings of the Advanced Data Mining and Applications - 13th International Conference, 2017

2016

Personalized and adaptive recommendation

Yong Liu

PhD thesis, 2016

Neighborhood Regularized Logistic Matrix Factorization for Drug-Target Interaction Prediction.

Yong Liu, Min Wu, Chunyan Miao, Peilin Zhao, Xiaoli Li

PLoS Comput. Biol., 2016

Learning Optimal Social Dependency for Recommendation.

Yong Liu, Peilin Zhao, Xin Liu, Min Wu, Xiaoli Li

CoRR, 2016

Exploring the Context of Locations for Personalized Location Recommendations.

Xin Liu, Yong Liu, Xiaoli Li

Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence, 2016

2015

A Boosting Algorithm for Item Recommendation with Implicit Feedback.

Yong Liu, Peilin Zhao, Aixin Sun, Chunyan Miao

Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence, 2015

2014

Your neighbors affect your ratings: on geographical neighborhood influence to rating prediction.

Longke Hu, Aixin Sun, Yong Liu

Proceedings of the 37th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2014

A Social Trust Model Considering Trustees' Influence.

Jian-Ping Mei, Han Yu, Yong Liu, Zhiqi Shen, Chunyan Miao

Proceedings of the PRIMA 2014: Principles and Practice of Multi-Agent Systems, 2014

Exploiting Geographical Neighborhood Characteristics for Location Recommendation.

Yong Liu, Wei Wei, Aixin Sun, Chunyan Miao

Proceedings of the 23rd ACM International Conference on Conference on Information and Knowledge Management, 2014

2013

Personalized point-of-interest recommendation by mining users' preference transition.

Xin Liu, Yong Liu, Karl Aberer, Chunyan Miao

Proceedings of the 22nd ACM International Conference on Information and Knowledge Management, 2013