Yiqi Wang

Orcid: 0000-0001-9594-1919

Affiliations:
  • Michigan State University, East Lansing, MI, USA


According to our database1, Yiqi Wang authored at least 35 papers between 2016 and 2023.

Collaborative distances:

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

Online presence:

On csauthors.net:

Bibliography

2023
An Adaptive Graph Pre-training Framework for Localized Collaborative Filtering.
ACM Trans. Inf. Syst., April, 2023

Trustworthy AI: A Computational Perspective.
ACM Trans. Intell. Syst. Technol., February, 2023

Recommender Systems in the Era of Large Language Models (LLMs).
CoRR, 2023

LinRec: Linear Attention Mechanism for Long-term Sequential Recommender Systems.
Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2023

AutoDPQ: Automated Differentiable Product Quantization for Embedding Compression.
Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2023

STRec: Sparse Transformer for Sequential Recommendations.
Proceedings of the 17th ACM Conference on Recommender Systems, 2023

PromptST: Prompt-Enhanced Spatio-Temporal Multi-Attribute Prediction.
Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023

Rethinking Sensors Modeling: Hierarchical Information Enhanced Traffic Forecasting.
Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023

Are Message Passing Neural Networks Really Helpful for Knowledge Graph Completion?
Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2023

2022
Test-Time Training for Graph Neural Networks.
CoRR, 2022

A Comprehensive Survey on Trustworthy Recommender Systems.
CoRR, 2022

Are Graph Neural Networks Really Helpful for Knowledge Graph Completion?
CoRR, 2022


Localized Graph Collaborative Filtering.
Proceedings of the 2022 SIAM International Conference on Data Mining, 2022

Graph Neural Networks for Multimodal Single-Cell Data Integration.
Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

HousE: Knowledge Graph Embedding with Householder Parameterization.
Proceedings of the International Conference on Machine Learning, 2022

2021
Gophormer: Ego-Graph Transformer for Node Classification.
CoRR, 2021

Localized Graph Collaborative Filtering.
CoRR, 2021

Trustworthy AI: A Computational Perspective.
CoRR, 2021

Node Similarity Preserving Graph Convolutional Networks.
Proceedings of the WSDM '21, 2021

Graph Representation Learning: Foundations, Methods, Applications and Systems.
Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

Elastic Graph Neural Networks.
Proceedings of the 38th International Conference on Machine Learning, 2021

2020
Adversarial Attacks and Defenses on Graphs.
SIGKDD Explor., 2020

Graph Convolutional Networks against Degree-Related Biases.
CoRR, 2020

Self-supervised Learning on Graphs: Deep Insights and New Direction.
CoRR, 2020

Non-IID Graph Neural Networks.
CoRR, 2020

Adversarial Attacks and Defenses on Graphs: A Review and Empirical Study.
CoRR, 2020

Traffic Flow Prediction via Spatial Temporal Graph Neural Network.
Proceedings of the WWW '20: The Web Conference 2020, Taipei, Taiwan, April 20-24, 2020, 2020

Deep Graph Learning: Foundations, Advances and Applications.
Proceedings of the KDD '20: The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2020

Graph Pooling with Representativeness.
Proceedings of the 20th IEEE International Conference on Data Mining, 2020

Mitigating Gender Bias for Neural Dialogue Generation with Adversarial Learning.
Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, 2020

Investigating and Mitigating Degree-Related Biases in Graph Convoltuional Networks.
Proceedings of the CIKM '20: The 29th ACM International Conference on Information and Knowledge Management, 2020

2018
Exploration of Human Activities Using Sensing Data via Deep Embedded Determination.
Proceedings of the Wireless Algorithms, Systems, and Applications, 2018

Deep Embedding for Determining the Number of Clusters.
Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2016
Application-Based Coarse-Grained Incremental Checkpointing Based on Non-volatile Memory.
Proceedings of the Network and Parallel Computing, 2016


  Loading...