Wanyu Lin

Orcid: 0000-0002-7328-8039

According to our database1, Wanyu Lin authored at least 27 papers between 2014 and 2024.

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Bibliography

2024
Personalized Federated Learning with Layer-Wise Feature Transformation via Meta-Learning.
ACM Trans. Knowl. Discov. Data, May, 2024

Status-Aware Signed Heterogeneous Network Embedding With Graph Neural Networks.
IEEE Trans. Neural Networks Learn. Syst., April, 2024

Generating Diagnostic and Actionable Explanations for Fair Graph Neural Networks.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

SelfPromer: Self-Prompt Dehazing Transformers with Depth-Consistency.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023
Personalized Federated Learning on Non-IID Data via Group-based Meta-learning.
ACM Trans. Knowl. Discov. Data, May, 2023

Improving Accuracy and Convergence in Group-Based Federated Learning on Non-IID Data.
IEEE Trans. Netw. Sci. Eng., 2023

A<sup>2</sup>S<sup>2</sup>-GNN: Rigging GNN-Based Social Status by Adversarial Attacks in Signed Social Networks.
IEEE Trans. Inf. Forensics Secur., 2023

Prototype Correction via Contrastive Augmentation for Few-Shot Unconstrained Palmprint Recognition.
IEEE Trans. Inf. Forensics Secur., 2023

Practical Differentially Private and Byzantine-resilient Federated Learning.
Proc. ACM Manag. Data, 2023

SelfPromer: Self-Prompt Dehazing Transformers with Depth-Consistency.
CoRR, 2023

SoftGPT: Learn Goal-Oriented Soft Object Manipulation Skills by Generative Pre-Trained Heterogeneous Graph Transformer.
IROS, 2023

Robust Graph Meta-Learning via Manifold Calibration with Proxy Subgraphs.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022
Towards Private Learning on Decentralized Graphs With Local Differential Privacy.
IEEE Trans. Inf. Forensics Secur., 2022

1st ICLR International Workshop on Privacy, Accountability, Interpretability, Robustness, Reasoning on Structured Data (PAIR^2Struct).
CoRR, 2022

OrphicX: A Causality-Inspired Latent Variable Model for Interpreting Graph Neural Networks.
CoRR, 2022

OrphicX: A Causality-Inspired Latent Variable Model for Interpreting Graph Neural Networks.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

2021
Privacy-Preserving Similarity Search With Efficient Updates in Distributed Key-Value Stores.
IEEE Trans. Parallel Distributed Syst., 2021

Medley: Predicting Social Trust in Time-Varying Online Social Networks.
Proceedings of the 40th IEEE Conference on Computer Communications, 2021

Generative Causal Explanations for Graph Neural Networks.
Proceedings of the 38th International Conference on Machine Learning, 2021

Hierarchical Deep Reinforcement Learning for Multi-robot Cooperation in Partially Observable Environment.
Proceedings of the Third IEEE International Conference on Cognitive Machine Intelligence, 2021

2020
Guardian: Evaluating Trust in Online Social Networks with Graph Convolutional Networks.
Proceedings of the 39th IEEE Conference on Computer Communications, 2020

Shoestring: Graph-Based Semi-Supervised Classification With Severely Limited Labeled Data.
Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

Adversarial Attacks on Link Prediction Algorithms Based on Graph Neural Networks.
Proceedings of the ASIA CCS '20: The 15th ACM Asia Conference on Computer and Communications Security, 2020

2019
Shoestring: Graph-Based Semi-Supervised Learning with Severely Limited Labeled Data.
CoRR, 2019

Distributed Least Squares Estimation Algorithms Design for Sensor Networks.
Ad Hoc Sens. Wirel. Networks, 2019

2017
Multi-Client Searchable Encryption over Distributed Key-Value Stores.
Proceedings of the 2017 IEEE International Conference on Smart Computing, 2017

2014
E<sup>3</sup>: Towards energy-efficient distributed least squares estimation in sensor networks.
Proceedings of the IEEE 22nd International Symposium of Quality of Service, 2014


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