Jian Lou

Orcid: 0000-0002-4110-2068

Affiliations:
  • Zhejiang University, China
  • Xidian University, China (former)
  • Emory University, Atlanta, GA, USA (former)
  • Hong Kong Baptist University, Kowloon, Hong Kong (former)


According to our database1, Jian Lou authored at least 70 papers between 2015 and 2024.

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

Timeline

Legend:

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Online presence:

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Bibliography

2024
Local Differentially Private Heavy Hitter Detection in Data Streams with Bounded Memory.
Proc. ACM Manag. Data, February, 2024

RemovalNet: DNN Fingerprint Removal Attacks.
IEEE Trans. Dependable Secur. Comput., 2024

MaskArmor: Confidence masking-based defense mechanism for GNN against MIA.
Inf. Sci., 2024

Machine Unlearning in Forgettability Sequence.
CoRR, 2024

Differentially Private Zeroth-Order Methods for Scalable Large Language Model Finetuning.
CoRR, 2024

Cross-silo Federated Learning with Record-level Personalized Differential Privacy.
CoRR, 2024

Contrastive Unlearning: A Contrastive Approach to Machine Unlearning.
CoRR, 2024

DPAR: Decoupled Graph Neural Networks with Node-Level Differential Privacy.
Proceedings of the ACM on Web Conference 2024, 2024

PromptCARE: Prompt Copyright Protection by Watermark Injection and Verification.
Proceedings of the IEEE Symposium on Security and Privacy, 2024

Balancing Generalization and Robustness in Adversarial Training via Steering through Clean and Adversarial Gradient Directions.
Proceedings of the 32nd ACM International Conference on Multimedia, MM 2024, Melbourne, VIC, Australia, 28 October 2024, 2024

PoisonPrompt: Backdoor Attack on Prompt-Based Large Language Models.
Proceedings of the IEEE International Conference on Acoustics, 2024

Does Differential Privacy Prevent Backdoor Attacks in Practice?
Proceedings of the Data and Applications Security and Privacy XXXVIII, 2024

Physical Backdoor: Towards Temperature-Based Backdoor Attacks in the Physical World.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

IGAMT: Privacy-Preserving Electronic Health Record Synthesization with Heterogeneity and Irregularity.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023
DP-starJ: A Differential Private Scheme towards Analytical Star-Join Queries.
Proc. ACM Manag. Data, December, 2023

Equitable Data Valuation Meets the Right to Be Forgotten in Model Markets.
Proc. VLDB Endow., 2023

Prompt Valuation Based on Shapley Values.
CoRR, 2023

ERASER: Machine Unlearning in MLaaS via an Inference Serving-Aware Approach.
CoRR, 2023

DP-starJ: A Differential Private Scheme towards Analytical Star-Join Queries.
CoRR, 2023

Wasserstein Adversarial Examples on Univariant Time Series Data.
CoRR, 2023

Federated Semi-Supervised Learning with Annotation Heterogeneity.
CoRR, 2023

Interpretation Attacks and Defenses on Predictive Models Using Electronic Health Records.
Proceedings of the Machine Learning and Knowledge Discovery in Databases: Research Track, 2023

CAPP-130: A Corpus of Chinese Application Privacy Policy Summarization and Interpretation.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Certified Minimax Unlearning with Generalization Rates and Deletion Capacity.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

ACQ: Few-shot Backdoor Defense via Activation Clipping and Quantizing.
Proceedings of the 31st ACM International Conference on Multimedia, 2023

MULTIPAR: Supervised Irregular Tensor Factorization with Multi-task Learning for Computational Phenotyping.
Proceedings of the Machine Learning for Health, 2023

MUter: Machine Unlearning on Adversarially Trained Models.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

Explaining Adversarial Robustness of Neural Networks from Clustering Effect Perspective.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

Closed-form Machine Unlearning for Matrix Factorization.
Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023

Personalized Differentially Private Federated Learning without Exposing Privacy Budgets.
Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023

FINER: Enhancing State-of-the-art Classifiers with Feature Attribution to Facilitate Security Analysis.
Proceedings of the 2023 ACM SIGSAC Conference on Computer and Communications Security, 2023

2022
Generating Adversarial Examples With Distance Constrained Adversarial Imitation Networks.
IEEE Trans. Dependable Secur. Comput., 2022

Robust Tensor SVD and Recovery With Rank Estimation.
IEEE Trans. Cybern., 2022

FedTracker: Furnishing Ownership Verification and Traceability for Federated Learning Model.
CoRR, 2022

Private Semi-supervised Knowledge Transfer for Deep Learning from Noisy Labels.
CoRR, 2022

Towards Training Graph Neural Networks with Node-Level Differential Privacy.
CoRR, 2022

MULTIPAR: Supervised Irregular Tensor Factorization with Multi-task Learning.
CoRR, 2022

Vertical Federated Principal Component Analysis and Its Kernel Extension on Feature-wise Distributed Data.
CoRR, 2022

Purifier: Plug-and-play Backdoor Mitigation for Pre-trained Models Via Anomaly Activation Suppression.
Proceedings of the MM '22: The 30th ACM International Conference on Multimedia, Lisboa, Portugal, October 10, 2022

Backdoor Attacks on Crowd Counting.
Proceedings of the MM '22: The 30th ACM International Conference on Multimedia, Lisboa, Portugal, October 10, 2022

Higher-Order Masked Graph Neural Networks for Traffic Flow Prediction.
Proceedings of the IEEE International Conference on Data Mining, 2022

RobustFed: A Truth Inference Approach for Robust Federated Learning.
Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022

DP-HORUS: Differentially Private Hierarchical Count Histograms under Untrusted Server.
Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022

2021
An Uplink Communication-Efficient Approach to Featurewise Distributed Sparse Optimization With Differential Privacy.
IEEE Trans. Neural Networks Learn. Syst., 2021

Demonstration of Dealer: An End-to-End Model Marketplace with Differential Privacy.
Proc. VLDB Endow., 2021

Projected Federated Averaging with Heterogeneous Differential Privacy.
Proc. VLDB Endow., 2021

Dealer: An End-to-End Model Marketplace with Differential Privacy.
Proc. VLDB Endow., 2021

SNEAK: Synonymous Sentences-Aware Adversarial Attack on Natural Language Video Localization.
CoRR, 2021

SemiFed: Semi-supervised Federated Learning with Consistency and Pseudo-Labeling.
CoRR, 2021

Communication Efficient Federated Generalized Tensor Factorization for Collaborative Health Data Analytics.
Proceedings of the WWW '21: The Web Conference 2021, 2021

Vertical Federated Principal Component Analysis on Feature-Wise Distributed Data.
Proceedings of the Web Information Systems Engineering - WISE 2021, 2021

Certified Robustness to Word Substitution Attack with Differential Privacy.
Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2021

Private Stochastic Non-convex Optimization with Improved Utility Rates.
Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021

Communication Efficient Tensor Factorization for Decentralized Healthcare Networks.
Proceedings of the IEEE International Conference on Data Mining, 2021

Integer-arithmetic-only Certified Robustness for Quantized Neural Networks.
Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

Temporal Network Embedding via Tensor Factorization.
Proceedings of the CIKM '21: The 30th ACM International Conference on Information and Knowledge Management, Virtual Event, Queensland, Australia, November 1, 2021

2020
Robust Low-Rank Tensor Minimization via a New Tensor Spectral k-Support Norm.
IEEE Trans. Image Process., 2020

Synergistic Generic Learning for Face Recognition From a Contaminated Single Sample per Person.
IEEE Trans. Inf. Forensics Secur., 2020

Projection-free Online Empirical Risk Minimization with Privacy-preserving and Privacy Expiration.
Proceedings of the IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology, 2020

Robust Irregular Tensor Factorization and Completion for Temporal Health Data Analysis.
Proceedings of the CIKM '20: The 29th ACM International Conference on Information and Knowledge Management, 2020

Broadening Differential Privacy for Deep Learning Against Model Inversion Attacks.
Proceedings of the 2020 IEEE International Conference on Big Data (IEEE BigData 2020), 2020

Towards Training Robust Private Aggregation of Teacher Ensembles Under Noisy Labels.
Proceedings of the 2020 IEEE International Conference on Big Data (IEEE BigData 2020), 2020

2019
Toward Efficient Image Representation: Sparse Concept Discriminant Matrix Factorization.
IEEE Trans. Circuits Syst. Video Technol., 2019

Sturm: Sparse Tubal-Regularized Multilinear Regression for fMRI.
Proceedings of the Machine Learning in Medical Imaging - 10th International Workshop, 2019

Privacy-Preserving Tensor Factorization for Collaborative Health Data Analysis.
Proceedings of the 28th ACM International Conference on Information and Knowledge Management, 2019

2018
Uplink Communication Efficient Differentially Private Sparse Optimization With Feature-Wise Distributed Data.
Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017
Proximal average approximated incremental gradient descent for composite penalty regularized empirical risk minimization.
Mach. Learn., 2017

2016
Scalable Spectral k-Support Norm Regularization for Robust Low Rank Subspace Learning.
Proceedings of the 25th ACM International Conference on Information and Knowledge Management, 2016

2015
Efficient Generalized Conditional Gradient with Gradient Sliding for Composite Optimization.
Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence, 2015

Proximal Average Approximated Incremental Gradient Method for Composite Penalty Regularized Empirical Risk Minimization.
Proceedings of The 7th Asian Conference on Machine Learning, 2015


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