2025
Rethinking Byzantine Robustness in Federated Recommendation from Sparse Aggregation Perspective.
CoRR, January, 2025
MLLM-as-a-Judge for Image Safety without Human Labeling.
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CoRR, January, 2025
2024
FedFAIM: A Model Performance-Based Fair Incentive Mechanism for Federated Learning.
IEEE Trans. Big Data, December, 2024
Practical Attribute Reconstruction Attack Against Federated Learning.
IEEE Trans. Big Data, December, 2024
FT-Shield: A Watermark Against Unauthorized Fine-tuning in Text-to-Image Diffusion Models.
SIGKDD Explor., December, 2024
Privacy and Robustness in Federated Learning: Attacks and Defenses.
IEEE Trans. Neural Networks Learn. Syst., July, 2024
ResFed: Communication0Efficient Federated Learning With Deep Compressed Residuals.
IEEE Internet Things J., March, 2024
EdgeDis: Enabling Fast, Economical, and Reliable Data Dissemination for Mobile Edge Computing.
IEEE Trans. Serv. Comput., 2024
${\sf FederBoost}$: Private Federated Learning for GBDT.
IEEE Trans. Dependable Secur. Comput., 2024
Integration of large language models and federated learning.
Patterns, 2024
Asymmetrical Reciprocity-based Federated Learning for Resolving Disparities in Medical Diagnosis.
CoRR, 2024
Rendering-Refined Stable Diffusion for Privacy Compliant Synthetic Data.
CoRR, 2024
MLAN: Language-Based Instruction Tuning Improves Zero-Shot Generalization of Multimodal Large Language Models.
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CoRR, 2024
Boundary Attention Constrained Zero-Shot Layout-To-Image Generation.
CoRR, 2024
Dual Low-Rank Adaptation for Continual Learning with Pre-Trained Models.
CoRR, 2024
Copyright-Aware Incentive Scheme for Generative Art Models Using Hierarchical Reinforcement Learning.
CoRR, 2024
Masked Differential Privacy.
CoRR, 2024
Self-Comparison for Dataset-Level Membership Inference in Large (Vision-)Language Models.
CoRR, 2024
RLCP: A Reinforcement Learning-based Copyright Protection Method for Text-to-Image Diffusion Model.
CoRR, 2024
CURE4Rec: A Benchmark for Recommendation Unlearning with Deeper Influence.
CoRR, 2024
Stretching Each Dollar: Diffusion Training from Scratch on a Micro-Budget.
CoRR, 2024
Six-CD: Benchmarking Concept Removals for Benign Text-to-image Diffusion Models.
CoRR, 2024
EnTruth: Enhancing the Traceability of Unauthorized Dataset Usage in Text-to-image Diffusion Models with Minimal and Robust Alterations.
CoRR, 2024
Towards Fundamentally Scalable Model Selection: Asymptotically Fast Update and Selection.
CoRR, 2024
Evaluating and Mitigating IP Infringement in Visual Generative AI.
CoRR, 2024
Federated Learning under Partially Class-Disjoint Data via Manifold Reshaping.
CoRR, 2024
Is Synthetic Image Useful for Transfer Learning? An Investigation into Data Generation, Volume, and Utilization.
CoRR, 2024
Unveiling the Secrets without Data: Can Graph Neural Networks Be Exploited through Data-Free Model Extraction Attacks?
Proceedings of the 33rd USENIX Security Symposium, 2024
Backdoor Attacks with Input-Unique Triggers in NLP.
Proceedings of the Machine Learning and Knowledge Discovery in Databases. Research Track, 2024
FLoRA: Federated Fine-Tuning Large Language Models with Heterogeneous Low-Rank Adaptations.
Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024
pFedClub: Controllable Heterogeneous Model Aggregation for Personalized Federated Learning.
Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024
CURE4Rec: A Benchmark for Recommendation Unlearning with Deeper Influence.
Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024
DECO-Bench: Unified Benchmark for Decoupled Task-Agnostic Synthetic Data Release.
Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024
FEDMEKI: A Benchmark for Scaling Medical Foundation Models via Federated Knowledge Injection.
Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024
Defending Against Weight-Poisoning Backdoor Attacks for Parameter-Efficient Fine-Tuning.
Proceedings of the Findings of the Association for Computational Linguistics: NAACL 2024, 2024
FedSAC: Dynamic Submodel Allocation for Collaborative Fairness in Federated Learning.
Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024
Protecting Split Learning by Potential Energy Loss.
Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence, 2024
COALA: A Practical and Vision-Centric Federated Learning Platform.
Proceedings of the Forty-first International Conference on Machine Learning, 2024
How to Trace Latent Generative Model Generated Images without Artificial Watermark?
Proceedings of the Forty-first International Conference on Machine Learning, 2024
PerceptAnon: Exploring the Human Perception of Image Anonymization Beyond Pseudonymization for GDPR.
Proceedings of the Forty-first International Conference on Machine Learning, 2024
Bridging Model Heterogeneity in Federated Learning via Uncertainty-based Asymmetrical Reciprocity Learning.
Proceedings of the Forty-first International Conference on Machine Learning, 2024
Effective Federated Graph Matching.
Proceedings of the Forty-first International Conference on Machine Learning, 2024
FedWon: Triumphing Multi-domain Federated Learning Without Normalization.
Proceedings of the Twelfth International Conference on Learning Representations, 2024
FedP3: Federated Personalized and Privacy-friendly Network Pruning under Model Heterogeneity.
Proceedings of the Twelfth International Conference on Learning Representations, 2024
Detecting, Explaining, and Mitigating Memorization in Diffusion Models.
Proceedings of the Twelfth International Conference on Learning Representations, 2024
DIAGNOSIS: Detecting Unauthorized Data Usages in Text-to-image Diffusion Models.
Proceedings of the Twelfth International Conference on Learning Representations, 2024
Unveiling and Mitigating Memorization in Text-to-Image Diffusion Models Through Cross Attention.
Proceedings of the Computer Vision - ECCV 2024, 2024
Finding Needles in a Haystack: A Black-Box Approach to Invisible Watermark Detection.
Proceedings of the Computer Vision - ECCV 2024, 2024
A Simple Background Augmentation Method for Object Detection with Diffusion Model.
Proceedings of the Computer Vision - ECCV 2024, 2024
FedMef: Towards Memory-Efficient Federated Dynamic Pruning.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 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
Federated Learning under Partially Disjoint Data via Manifold Reshaping.
Trans. Mach. Learn. Res., 2023
Turning a Curse into a Blessing: Enabling In-Distribution-Data-Free Backdoor Removal via Stabilized Model Inversion.
Trans. Mach. Learn. Res., 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
Privacy-preserving design of graph neural networks with applications to vertical federated learning.
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.
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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
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