Junliang Yu

Orcid: 0000-0003-3401-9829

According to our database1, Junliang Yu authored at least 54 papers between 2017 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

Online presence:

On csauthors.net:

Bibliography

2024
XSimGCL: Towards Extremely Simple Graph Contrastive Learning for Recommendation.
IEEE Trans. Knowl. Data Eng., February, 2024

Self-Supervised Learning for Recommender Systems: A Survey.
IEEE Trans. Knowl. Data Eng., January, 2024

A Survey on Point-of-Interest Recommendation: Models, Architectures, and Security.
CoRR, 2024

LLM-Powered Text Simulation Attack Against ID-Free Recommender Systems.
CoRR, 2024

Poisoning Attacks and Defenses in Recommender Systems: A Survey.
CoRR, 2024

Rethinking and Accelerating Graph Condensation: A Training-Free Approach with Class Partition.
CoRR, 2024

Graph Condensation: A Survey.
CoRR, 2024

Poisoning Attacks against Recommender Systems: A Survey.
CoRR, 2024

Prompt-enhanced Federated Content Representation Learning for Cross-domain Recommendation.
Proceedings of the ACM on Web Conference 2024, 2024

Motif-based Prompt Learning for Universal Cross-domain Recommendation.
Proceedings of the 17th ACM International Conference on Web Search and Data Mining, 2024

Consistency and Discrepancy-Based Contrastive Tripartite Graph Learning for Recommendations.
Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024

Unveiling Vulnerabilities of Contrastive Recommender Systems to Poisoning Attacks.
Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024

Accelerating Scalable Graph Neural Network Inference with Node-Adaptive Propagation.
Proceedings of the 40th IEEE International Conference on Data Engineering, 2024

2023
Efficient On-Device Session-Based Recommendation.
ACM Trans. Inf. Syst., October, 2023

Predictive and Contrastive: Dual-Auxiliary Learning for Recommendation.
IEEE Trans. Comput. Soc. Syst., October, 2023

Who are the Best Adopters? User Selection Model for Free Trial Item Promotion.
IEEE Trans. Big Data, April, 2023

Enhancing recommender systems with self-supervised learning
PhD thesis, 2023

Poisoning Attacks Against Contrastive Recommender Systems.
CoRR, 2023

Efficient Bi-Level Optimization for Recommendation Denoising.
Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

Semantic-aware Node Synthesis for Imbalanced Heterogeneous Information Networks.
Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023

Towards Communication-Efficient Model Updating for On-Device Session-Based Recommendation.
Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023

2022
Fast-adapting and privacy-preserving federated recommender system.
VLDB J., 2022

Enhancing Social Recommendation With Adversarial Graph Convolutional Networks.
IEEE Trans. Knowl. Data Eng., 2022

Addressing the Extreme Cold-Start Problem in Group Recommendation.
CoRR, 2022


Are Graph Augmentations Necessary?: Simple Graph Contrastive Learning for Recommendation.
Proceedings of the SIGIR '22: The 45th International ACM SIGIR Conference on Research and Development in Information Retrieval, Madrid, Spain, July 11, 2022

On-Device Next-Item Recommendation with Self-Supervised Knowledge Distillation.
Proceedings of the SIGIR '22: The 45th International ACM SIGIR Conference on Research and Development in Information Retrieval, Madrid, Spain, July 11, 2022

2021
Ready for emerging threats to recommender systems? A graph convolution-based generative shilling attack.
Inf. Sci., 2021

Recommender systems based on generative adversarial networks: A problem-driven perspective.
Inf. Sci., 2021

Path-based reasoning over heterogeneous networks for recommendation via bidirectional modeling.
Neurocomputing, 2021

Graph Augmentation-Free Contrastive Learning for Recommendation.
CoRR, 2021

Ready for Emerging Threats to Recommender Systems? A Graph Convolution-based Generative Shilling Attack.
CoRR, 2021

Self-Supervised Multi-Channel Hypergraph Convolutional Network for Social Recommendation.
Proceedings of the WWW '21: The Web Conference 2021, 2021

Socially-Aware Self-Supervised Tri-Training for Recommendation.
Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

Double-Scale Self-Supervised Hypergraph Learning for Group Recommendation.
Proceedings of the CIKM '21: The 30th ACM International Conference on Information and Knowledge Management, Virtual Event, Queensland, Australia, November 1, 2021

Self-Supervised Graph Co-Training for Session-based Recommendation.
Proceedings of the CIKM '21: The 30th ACM International Conference on Information and Knowledge Management, Virtual Event, Queensland, Australia, November 1, 2021

Self-Supervised Hypergraph Convolutional Networks for Session-based Recommendation.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020
Enhance Social Recommendation with Adversarial Graph Convolutional Networks.
CoRR, 2020

2019
A Minimax Game for Generative and Discriminative Sample Models for Recommendation.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2019

Nonlinear Transformation for Multiple Auxiliary Information in Music Recommendation.
Proceedings of the International Joint Conference on Neural Networks, 2019

Generating Reliable Friends via Adversarial Training to Improve Social Recommendation.
Proceedings of the 2019 IEEE International Conference on Data Mining, 2019

2018
融合矩阵分解与距离度量学习的社会化推荐算法 (Social Recommendation Method Integrating Matrix Factorization and Distance Metric Learning).
计算机科学, 2018

Detection of Shilling Attack Based on Bayesian Model and User Embedding.
Proceedings of the IEEE 30th International Conference on Tools with Artificial Intelligence, 2018

Social Recommendation Based on Implicit Friends Discovering Via Meta-Path.
Proceedings of the IEEE 30th International Conference on Tools with Artificial Intelligence, 2018

Meta-path Based Heterogeneous Graph Embedding for Music Recommendation.
Proceedings of the Neural Information Processing - 25th International Conference, 2018

Adaptive Implicit Friends Identification over Heterogeneous Network for Social Recommendation.
Proceedings of the 27th ACM International Conference on Information and Knowledge Management, 2018

2017
A Social Recommender Based on Factorization and Distance Metric Learning.
IEEE Access, 2017

Connecting Factorization and Distance Metric Learning for Social Recommendations.
Proceedings of the Knowledge Science, Engineering and Management, 2017

Make Users and Preferred Items Closer: Recommendation via Distance Metric Learning.
Proceedings of the Neural Information Processing - 24th International Conference, 2017

PUD: Social Spammer Detection Based on PU Learning.
Proceedings of the Neural Information Processing - 24th International Conference, 2017

Impact of the Important Users on Social Recommendation System.
Proceedings of the Collaborative Computing: Networking, Applications and Worksharing, 2017

Integrating User Embedding and Collaborative Filtering for Social Recommendations.
Proceedings of the Collaborative Computing: Networking, Applications and Worksharing, 2017

PUED: A Social Spammer Detection Method Based on PU Learning and Ensemble Learning.
Proceedings of the Collaborative Computing: Networking, Applications and Worksharing, 2017

Collaborative Shilling Detection Bridging Factorization and User Embedding.
Proceedings of the Collaborative Computing: Networking, Applications and Worksharing, 2017


  Loading...