Jiahao Ding

Orcid: 0000-0002-2867-4133

According to our database1, Jiahao Ding authored at least 29 papers between 2018 and 2024.

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

Timeline

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Links

On csauthors.net:

Bibliography

2024
Personalized 3D Location Privacy Protection With Differential and Distortion Geo-Perturbation.
IEEE Trans. Dependable Secur. Comput., 2024

2023
Stochastic privacy-preserving methods for nonconvex sparse learning.
Inf. Sci., June, 2023

PMP: Privacy-Aware Matrix Profile against Sensitive Pattern Inference for Time Series.
Proceedings of the 2023 SIAM International Conference on Data Mining, 2023

An Adaptive RRT Algorithm Based on Narrow Passage Recognition for Assembly Path Planning.
Proceedings of the IEEE International Conference on Industrial Engineering and Engineering Management, 2023

Finite Sample Guarantees of Differentially Private Expectation Maximization Algorithm.
Proceedings of the ECAI 2023 - 26th European Conference on Artificial Intelligence, September 30 - October 4, 2023, Kraków, Poland, 2023

2022
3D Geo-Indistinguishability for Indoor Location-Based Services.
IEEE Trans. Wirel. Commun., 2022

Private Empirical Risk Minimization With Analytic Gaussian Mechanism for Healthcare System.
IEEE Trans. Big Data, 2022

Towards Fast and Accurate Federated Learning with Non-IID Data for Cloud-Based IoT Applications.
J. Circuits Syst. Comput., 2022

IoT Device Friendly and Communication-Efficient Federated Learning via Joint Model Pruning and Quantization.
IEEE Internet Things J., 2022

Federated Optimization of ℓ0-norm Regularized Sparse Learning.
Algorithms, 2022

2021
Incentivizing Differentially Private Federated Learning: A Multidimensional Contract Approach.
IEEE Internet Things J., 2021

Adaptive Privacy Preserving Deep Learning Algorithms for Medical Data.
Proceedings of the IEEE Winter Conference on Applications of Computer Vision, 2021

SQuaFL: Sketch-Quantization Inspired Communication Efficient Federated Learning.
Proceedings of the 6th IEEE/ACM Symposium on Edge Computing, 2021

To Talk or to Work: Delay Efficient Federated Learning over Mobile Edge Devices.
Proceedings of the IEEE Global Communications Conference, 2021

Differentially Private and Communication Efficient Collaborative Learning.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020
Evaluation of Inference Attack Models for Deep Learning on Medical Data.
CoRR, 2020

Differentially Private (Gradient) Expectation Maximization Algorithm with Statistical Guarantees.
CoRR, 2020

Effective Proximal Methods for Non-convex Non-smooth Regularized Learning.
Proceedings of the 20th IEEE International Conference on Data Mining, 2020

Mobile Crowdsensing Task Allocation optimization with Differentially Private Location Privacy.
Proceedings of the 2020 IEEE International Conference on Communications, 2020

AR Assisted Process Guidance System for Ship Block Fabrication.
Proceedings of the Virtual, Augmented and Mixed Reality. Industrial and Everyday Life Applications, 2020

Privacy Preserving Facial Recognition Against Model Inversion Attacks.
Proceedings of the IEEE Global Communications Conference, 2020

Towards Plausible Differentially Private ADMM Based Distributed Machine Learning.
Proceedings of the CIKM '20: The 29th ACM International Conference on Information and Knowledge Management, 2020

Differentially Private and Fair Classification via Calibrated Functional Mechanism.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019
Deep Q-Network-Based Route Scheduling for TNC Vehicles With Passengers' Location Differential Privacy.
IEEE Internet Things J., 2019

Optimal Differentially Private ADMM for Distributed Machine Learning.
CoRR, 2019

Stochastic ADMM Based Distributed Machine Learning with Differential Privacy.
Proceedings of the Security and Privacy in Communication Networks, 2019

Differentially Private Functional Mechanism for Generative Adversarial Networks.
Proceedings of the 2019 IEEE Global Communications Conference, 2019

Differentially Private Robust ADMM for Distributed Machine Learning.
Proceedings of the 2019 IEEE International Conference on Big Data (IEEE BigData), 2019

2018
Deep Q-Network Based Route Scheduling for Transportation Network Company Vehicles.
Proceedings of the IEEE Global Communications Conference, 2018


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