Lingjuan Lyu

Orcid: 0000-0003-3170-4994

According to our database1, Lingjuan Lyu authored at least 150 papers between 2016 and 2024.

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Bibliography

2024
ResFed: Communication0Efficient Federated Learning With Deep Compressed Residuals.
IEEE Internet Things J., March, 2024

Is Synthetic Image Useful for Transfer Learning? An Investigation into Data Generation, Volume, and Utilization.
CoRR, 2024

Finding needles in a haystack: A Black-Box Approach to Invisible Watermark Detection.
CoRR, 2024

FedMef: Towards Memory-efficient Federated Dynamic Pruning.
CoRR, 2024

Unveiling and Mitigating Memorization in Text-to-image Diffusion Models through Cross Attention.
CoRR, 2024

Minimum Topology Attacks for Graph Neural Networks.
CoRR, 2024

Defending Against Weight-Poisoning Backdoor Attacks for Parameter-Efficient Fine-Tuning.
CoRR, 2024

2023
Haze Visibility Enhancement for Promoting Traffic Situational Awareness in Vision-Enabled Intelligent Transportation.
IEEE Trans. Veh. Technol., December, 2023

Defending ChatGPT against jailbreak attack via self-reminders.
Nat. Mac. Intell., December, 2023

InOR-Net: Incremental 3-D Object Recognition Network for Point Cloud Representation.
IEEE Trans. Neural Networks Learn. Syst., October, 2023

Traffic Anomaly Prediction Based on Joint Static-Dynamic Spatio-Temporal Evolutionary Learning.
IEEE Trans. Knowl. Data Eng., May, 2023

Decision Boundary-Aware Data Augmentation for Adversarial Training.
IEEE Trans. Dependable Secur. Comput., 2023

Correction to "Privacy-Preserving Blockchain-Based Federated Learning for IoT Devices".
IEEE Internet Things J., 2023

EdgeDis: Enabling Fast, Economical, and Reliable Data Dissemination for Mobile Edge Computing.
CoRR, 2023

Privacy-preserving design of graph neural networks with applications to vertical federated learning.
CoRR, 2023

Towards Personalized Federated Learning via Heterogeneous Model Reassembly.
CoRR, 2023

FROD: Robust Object Detection for Free.
CoRR, 2023

Federated Learning over a Wireless Network: Distributed User Selection through Random Access.
CoRR, 2023

How to Detect Unauthorized Data Usages in Text-to-image Diffusion Models.
CoRR, 2023

When Foundation Model Meets Federated Learning: Motivations, Challenges, and Future Directions.
CoRR, 2023

Pushing the Limits of ChatGPT on NLP Tasks.
CoRR, 2023

Is Normalization Indispensable for Multi-domain Federated Learning?
CoRR, 2023

Alteration-free and Model-agnostic Origin Attribution of Generated Images.
CoRR, 2023

V2X-Boosted Federated Learning for Cooperative Intelligent Transportation Systems with Contextual Client Selection.
CoRR, 2023

DADFNet: Dual Attention and Dual Frequency-Guided Dehazing Network for Video-Empowered Intelligent Transportation.
CoRR, 2023

Backdoor Attacks with Input-unique Triggers in NLP.
CoRR, 2023

A Pathway Towards Responsible AI Generated Content.
CoRR, 2023

On the Hardness of Robustness Transfer: A Perspective from Rademacher Complexity over Symmetric Difference Hypothesis Space.
CoRR, 2023

InOR-Net: Incremental 3D Object Recognition Network for Point Cloud Representation.
CoRR, 2023

GAIN: Enhancing Byzantine Robustness in Federated Learning with Gradient Decomposition.
CoRR, 2023

SplitGNN: Splitting GNN for Node Classification with Heterogeneous Attention.
CoRR, 2023

Differentially private locality sensitive hashing based federated recommender system.
Concurr. Comput. Pract. Exp., 2023

Minimum Topology Attacks for Graph Neural Networks.
Proceedings of the ACM Web Conference 2023, 2023

Multiple-Agent Deep Reinforcement Learning for Avatar Migration in Vehicular Metaverses.
Proceedings of the Companion Proceedings of the ACM Web Conference 2023, 2023

Meta-Sift: How to Sift Out a Clean Subset in the Presence of Data Poisoning?
Proceedings of the 32nd USENIX Security Symposium, 2023

ASSET: Robust Backdoor Data Detection Across a Multiplicity of Deep Learning Paradigms.
Proceedings of the 32nd USENIX Security Symposium, 2023

Towards Personalized Federated Learning via Heterogeneous Model Reassembly.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Where Did I Come From? Origin Attribution of AI-Generated Images.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Is Heterogeneity Notorious? Taming Heterogeneity to Handle Test-Time Shift in Federated Learning.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Privacy Assessment on Reconstructed Images: Are Existing Evaluation Metrics Faithful to Human Perception?
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

UltraRE: Enhancing RecEraser for Recommendation Unlearning via Error Decomposition.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

PrivateRec: Differentially Private Model Training and Online Serving for Federated News Recommendation.
Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

International Workshop on Federated Learning for Distributed Data Mining.
Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

Reducing Communication for Split Learning by Randomized Top-k Sparsification.
Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023

FedSampling: A Better Sampling Strategy for Federated Learning.
Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023

RAIN: RegulArization on Input and Network for Black-Box Domain Adaptation.
Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023

A Pathway Towards Responsible AI Generated Content.
Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023

Byzantine-Robust Learning on Heterogeneous Data via Gradient Splitting.
Proceedings of the International Conference on Machine Learning, 2023

Reconstructive Neuron Pruning for Backdoor Defense.
Proceedings of the International Conference on Machine Learning, 2023

Revisiting Data-Free Knowledge Distillation with Poisoned Teachers.
Proceedings of the International Conference on Machine Learning, 2023

Fast Federated Machine Unlearning with Nonlinear Functional Theory.
Proceedings of the International Conference on Machine Learning, 2023

Dimension-independent Certified Neural Network Watermarks via Mollifier Smoothing.
Proceedings of the International Conference on Machine Learning, 2023

IDEAL: Query-Efficient Data-Free Learning from Black-Box Models.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Towards Robustness Certification Against Universal Perturbations.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Deja Vu: Continual Model Generalization for Unseen Domains.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

MocoSFL: enabling cross-client collaborative self-supervised learning.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

MECTA: Memory-Economic Continual Test-Time Model Adaptation.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

MAS: Towards Resource-Efficient Federated Multiple-Task Learning.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

TARGET: Federated Class-Continual Learning via Exemplar-Free Distillation.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

The Perils of Learning From Unlabeled Data: Backdoor Attacks on Semi-supervised Learning.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

Towards Adversarially Robust Continual Learning.
Proceedings of the IEEE International Conference on Acoustics, 2023

Narcissus: A Practical Clean-Label Backdoor Attack with Limited Information.
Proceedings of the 2023 ACM SIGSAC Conference on Computer and Communications Security, 2023

GNN-SL: Sequence Labeling Based on Nearest Examples via GNN.
Proceedings of the Findings of the Association for Computational Linguistics: ACL 2023, 2023

Are You Copying My Model? Protecting the Copyright of Large Language Models for EaaS via Backdoor Watermark.
Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2023

Defending against Backdoor Attacks in Natural Language Generation.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

Delving into the Adversarial Robustness of Federated Learning.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022
Joint Stance and Rumor Detection in Hierarchical Heterogeneous Graph.
IEEE Trans. Neural Networks Learn. Syst., 2022

FedCTR: Federated Native Ad CTR Prediction with Cross-platform User Behavior Data.
ACM Trans. Intell. Syst. Technol., 2022

FedBERT: When Federated Learning Meets Pre-training.
ACM Trans. Intell. Syst. Technol., 2022

Privacy-Preserving Anomaly Detection in Cloud Manufacturing Via Federated Transformer.
IEEE Trans. Ind. Informatics, 2022

FLEAM: A Federated Learning Empowered Architecture to Mitigate DDoS in Industrial IoT.
IEEE Trans. Ind. Informatics, 2022

How to Democratise and Protect AI: Fair and Differentially Private Decentralised Deep Learning.
IEEE Trans. Dependable Secur. Comput., 2022

Cloud-Based Privacy-Preserving Collaborative Consumption for Sharing Economy.
IEEE Trans. Cloud Comput., 2022

Data Poisoning Attacks on Federated Machine Learning.
IEEE Internet Things J., 2022

ResFed: Communication Efficient Federated Learning by Transmitting Deep Compressed Residuals.
CoRR, 2022

How to Sift Out a Clean Data Subset in the Presence of Data Poisoning?
CoRR, 2022

Toward Better Target Representation for Source-Free and Black-Box Domain Adaptation.
CoRR, 2022

FairVFL: A Fair Vertical Federated Learning Framework with Contrastive Adversarial Learning.
CoRR, 2022

QEKD: Query-Efficient and Data-Free Knowledge Distillation from Black-box Models.
CoRR, 2022

PrivateRec: Differentially Private Training and Serving for Federated News Recommendation.
CoRR, 2022

Exploiting Data Sparsity in Secure Cross-Platform Social Recommendation.
CoRR, 2022

Threats to Pre-trained Language Models: Survey and Taxonomy.
CoRR, 2022

Differential Private Knowledge Transfer for Privacy-Preserving Cross-Domain Recommendation.
Proceedings of the WWW '22: The ACM Web Conference 2022, Virtual Event, Lyon, France, April 25, 2022

Prompt Certified Machine Unlearning with Randomized Gradient Smoothing and Quantization.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

FairVFL: A Fair Vertical Federated Learning Framework with Contrastive Adversarial Learning.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Outsourcing Training without Uploading Data via Efficient Collaborative Open-Source Sampling.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

CATER: Intellectual Property Protection on Text Generation APIs via Conditional Watermarks.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

CalFAT: Calibrated Federated Adversarial Training with Label Skewness.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

DENSE: Data-Free One-Shot Federated Learning.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

No One Left Behind: Inclusive Federated Learning over Heterogeneous Devices.
Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

EdgeWatch: Collaborative Investigation of Data Integrity at the Edge based on Blockchain.
Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

Data-Free Adversarial Knowledge Distillation for Graph Neural Networks.
Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022

Vertically Federated Graph Neural Network for Privacy-Preserving Node Classification.
Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022

Accelerated Federated Learning with Decoupled Adaptive Optimization.
Proceedings of the International Conference on Machine Learning, 2022

Privacy for Free: How does Dataset Condensation Help Privacy?
Proceedings of the International Conference on Machine Learning, 2022

How to Inject Backdoors with Better Consistency: Logit Anchoring on Clean Data.
Proceedings of the Tenth International Conference on Learning Representations, 2022

FedSkip: Combatting Statistical Heterogeneity with Federated Skip Aggregation.
Proceedings of the IEEE International Conference on Data Mining, 2022

Heterogeneous Graph Node Classification With Multi-Hops Relation Features.
Proceedings of the IEEE International Conference on Acoustics, 2022

Fine-mixing: Mitigating Backdoors in Fine-tuned Language Models.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2022, 2022

Extracted BERT Model Leaks More Information than You Think!
Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, 2022

Student Surpasses Teacher: Imitation Attack for Black-Box NLP APIs.
Proceedings of the 29th International Conference on Computational Linguistics, 2022

The 1st International Workshop on Federated Learning with Graph Data (FedGraph).
Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022

Cross-Network Social User Embedding with Hybrid Differential Privacy Guarantees.
Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022

Protecting Intellectual Property of Language Generation APIs with Lexical Watermark.
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021
Clustering-based Efficient Privacy-preserving Face Recognition Scheme without Compromising Accuracy.
ACM Trans. Sens. Networks, 2021

Local Differential Privacy-Based Federated Learning for Internet of Things.
IEEE Internet Things J., 2021

Privacy-Preserving Blockchain-Based Federated Learning for IoT Devices.
IEEE Internet Things J., 2021

A fast and scalable authentication scheme in IOT for smart living.
Future Gener. Comput. Syst., 2021

A Practical Data-Free Approach to One-shot Federated Learning with Heterogeneity.
CoRR, 2021

Beyond Model Extraction: Imitation Attack for Black-Box NLP APIs.
CoRR, 2021

FedKD: Communication Efficient Federated Learning via Knowledge Distillation.
CoRR, 2021

A Novel Attribute Reconstruction Attack in Federated Learning.
CoRR, 2021

A Vertical Federated Learning Framework for Graph Convolutional Network.
CoRR, 2021

Killing Two Birds with One Stone: Stealing Model and Inferring Attribute from BERT-based APIs.
CoRR, 2021

DP-SIGNSGD: When Efficiency Meets Privacy and Robustness.
CoRR, 2021

Robust Training Using Natural Transformation.
CoRR, 2021

Gradient Driven Rewards to Guarantee Fairness in Collaborative Machine Learning.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Anti-Backdoor Learning: Training Clean Models on Poisoned Data.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Exploiting Data Sparsity in Secure Cross-Platform Social Recommendation.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Model Extraction and Adversarial Transferability, Your BERT is Vulnerable!
Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2021

Federated Model Distillation with Noise-Free Differential Privacy.
Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021

Neural Attention Distillation: Erasing Backdoor Triggers from Deep Neural Networks.
Proceedings of the 9th International Conference on Learning Representations, 2021

Privacy-Preserving Optimal Insulin Dosing Decision.
Proceedings of the IEEE International Conference on Acoustics, 2021

Reliable and Privacy-Preserving Task Matching in Blockchain-Based Crowdsourcing.
Proceedings of the CIKM '21: The 30th ACM International Conference on Information and Knowledge Management, Virtual Event, Queensland, Australia, November 1, 2021

2020
Collaborative Fairness in Federated Learning.
Proceedings of the Federated Learning - Privacy and Incentive, 2020

Threats to Federated Learning.
Proceedings of the Federated Learning - Privacy and Incentive, 2020

Towards Fair and Privacy-Preserving Federated Deep Models.
IEEE Trans. Parallel Distributed Syst., 2020

FORESEEN: Towards Differentially Private Deep Inference for Intelligent Internet of Things.
IEEE J. Sel. Areas Commun., 2020

Privacy and Robustness in Federated Learning: Attacks and Defenses.
CoRR, 2020

Towards Building a Robust and Fair Federated Learning System.
CoRR, 2020

Collaborative Fairness in Federated Learning.
CoRR, 2020

Local Differential Privacy and Its Applications: A Comprehensive Survey.
CoRR, 2020

Threats to Federated Learning: A Survey.
CoRR, 2020

An Unsupervised PM2.5 Estimation Method With Different Spatio-Temporal Resolutions Based on KIDW-TCGRU.
IEEE Access, 2020

Contour Accentuation for Transfer Learning-Based Ship Recognition Method.
Proceedings of the Companion of The 2020 Web Conference 2020, 2020

Privacy-Preserving Data Generation and Sharing Using Identification Sanitizer.
Proceedings of the Web Information Systems Engineering - WISE 2020, 2020

Towards Distributed Privacy-Preserving Prediction.
Proceedings of the 2020 IEEE International Conference on Systems, Man, and Cybernetics, 2020

Towards Differentially Private Text Representations.
Proceedings of the 43rd International ACM SIGIR conference on research and development in Information Retrieval, 2020

Differentially Private Knowledge Distillation for Mobile Analytics.
Proceedings of the 43rd International ACM SIGIR conference on research and development in Information Retrieval, 2020

Lightweight Crypto-Assisted Distributed Differential Privacy for Privacy-Preserving Distributed Learning.
Proceedings of the 2020 International Joint Conference on Neural Networks, 2020

Differentially Private Representation for NLP: Formal Guarantee and An Empirical Study on Privacy and Fairness.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2020, 2020

2019
Fog-Embedded Deep Learning for the Internet of Things.
IEEE Trans. Ind. Informatics, 2019

Distributed Privacy-Preserving Prediction.
CoRR, 2019

Towards Fair and Decentralized Privacy-Preserving Deep Learning with Blockchain.
CoRR, 2019

2018
PPFA: Privacy Preserving Fog-Enabled Aggregation in Smart Grid.
IEEE Trans. Ind. Informatics, 2018

Privacy-preserving collaborative fuzzy clustering.
Data Knowl. Eng., 2018

2017
Fog-Empowered Anomaly Detection in IoT Using Hyperellipsoidal Clustering.
IEEE Internet Things J., 2017

Privacy-Preserving Aggregation of Smart Metering via Transformation and Encryption.
Proceedings of the 2017 IEEE Trustcom/BigDataSE/ICESS, Sydney, Australia, August 1-4, 2017, 2017

Privacy-Preserving Collaborative Deep Learning with Application to Human Activity Recognition.
Proceedings of the 2017 ACM on Conference on Information and Knowledge Management, 2017

2016
An improved scheme for privacy-preserving collaborative anomaly detection.
Proceedings of the 2016 IEEE International Conference on Pervasive Computing and Communication Workshops, 2016


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