Meng Hao

Orcid: 0009-0002-4405-9162

According to our database1, Meng Hao authored at least 42 papers between 2016 and 2024.

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Bibliography

2024
SVFGNN: A privacy-preserving vertical federated graph neural network model training framework based on split learning.
Peer Peer Netw. Appl., January, 2024

Model-Free GPU Online Energy Optimization.
IEEE Trans. Sustain. Comput., 2024

Research and Application of Artificial Intelligence in Power Smart Constuction Site.
Proceedings of the 2024 8th International Conference on Control Engineering and Artificial Intelligence, 2024

2023
Facial expression recognition based on regional adaptive correlation.
IET Comput. Vis., June, 2023

ESA-FedGNN: Efficient secure aggregation for federated graph neural networks.
Peer Peer Netw. Appl., March, 2023

FastSecNet: An Efficient Cryptographic Framework for Private Neural Network Inference.
IEEE Trans. Inf. Forensics Secur., 2023

PriVDT: An Efficient Two-Party Cryptographic Framework for Vertical Decision Trees.
IEEE Trans. Inf. Forensics Secur., 2023

Unbalanced Circuit-PSI from Oblivious Key-Value Retrieval.
IACR Cryptol. ePrint Arch., 2023

Evaluating the Generation Capabilities of Large Chinese Language Models.
CoRR, 2023

Extracting Cloud-based Model with Prior Knowledge.
CoRR, 2023

GuardHFL: Privacy Guardian for Heterogeneous Federated Learning.
Proceedings of the International Conference on Machine Learning, 2023

Toward Efficient and End-to-End Privacy-Preserving Distributed Gradient Boosting Decision Trees.
Proceedings of the IEEE International Conference on Communications, 2023

TriFSS: Secure Trigonometric Function Evaluation via Function Secret Sharing.
Proceedings of the IEEE International Conference on Communications, 2023

SecMath: An Efficient 2-Party Cryptographic Framework for Math Functions.
Proceedings of the IEEE International Conference on Communications, 2023

Membership Inference Attacks Against the Graph Classification.
Proceedings of the IEEE Global Communications Conference, 2023

Practical and Privacy-Preserving Density-Based Clustering via Shuffling.
Proceedings of the IEEE Global Communications Conference, 2023

Privacy-Preserving and Verifiable Outsourcing Inference Against Malicious Servers.
Proceedings of the IEEE Global Communications Conference, 2023

2022
Dynamic GPU Energy Optimization for Machine Learning Training Workloads.
IEEE Trans. Parallel Distributed Syst., 2022

Online Power Management for Multi-Cores: A Reinforcement Learning Based Approach.
IEEE Trans. Parallel Distributed Syst., 2022

Practical Membership Inference Attack Against Collaborative Inference in Industrial IoT.
IEEE Trans. Ind. Informatics, 2022

Big Data Analysis of Water Saving Standard Based on Bibliometrics.
J. Sensors, 2022

Iron: Private Inference on Transformers.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Secure Feature Selection for Vertical Federated Learning in eHealth Systems.
Proceedings of the IEEE International Conference on Communications, 2022

Efficient and Privacy-Preserving Federated Learning with Irregular Users.
Proceedings of the IEEE International Conference on Communications, 2022

CryptoFE: Practical and Privacy-Preserving Federated Learning via Functional Encryption.
Proceedings of the IEEE Global Communications Conference, 2022

Fast Secure Aggregation for Privacy-Preserving Federated Learning.
Proceedings of the IEEE Global Communications Conference, 2022

2021
Fine-Grained Powercap Allocation for Power-Constrained Systems Based on Multi-Objective Machine Learning.
IEEE Trans. Parallel Distributed Syst., 2021

Automatic translation of data parallel programs for heterogeneous parallelism through OpenMP offloading.
J. Supercomput., 2021

Enhanced Mixup Training: a Defense Method Against Membership Inference Attack.
Proceedings of the Information Security Practice and Experience: 16th International Conference, 2021

Towards Lightweight and Efficient Distributed Intrusion Detection Framework.
Proceedings of the IEEE Global Communications Conference, 2021

Efficient, Private and Robust Federated Learning.
Proceedings of the ACSAC '21: Annual Computer Security Applications Conference, Virtual Event, USA, December 6, 2021

2020
Efficient and Privacy-Enhanced Federated Learning for Industrial Artificial Intelligence.
IEEE Trans. Ind. Informatics, 2020

FreeTrack: Device-Free Human Tracking With Deep Neural Networks and Particle Filtering.
IEEE Syst. J., 2020

Privacy-aware and Resource-saving Collaborative Learning for Healthcare in Cloud Computing.
Proceedings of the 2020 IEEE International Conference on Communications, 2020

2019
Automatic generation of benchmarks for I/O-intensive parallel applications.
J. Parallel Distributed Comput., 2019

Multi-Parameter Performance Modeling Based on Machine Learning with Basic Block Features.
Proceedings of the 2019 IEEE Intl Conf on Parallel & Distributed Processing with Applications, 2019

Towards Efficient and Privacy-Preserving Federated Deep Learning.
Proceedings of the 2019 IEEE International Conference on Communications, 2019

PROFPRED: A Compiler-Level IR Based Performance Prediction Framework for MPI Industrial Applications.
Proceedings of the 21st IEEE International Conference on High Performance Computing and Communications; 17th IEEE International Conference on Smart City; 5th IEEE International Conference on Data Science and Systems, 2019

2018
knnAUC: an open-source R package for detecting nonlinear dependence between one continuous variable and one binary variable.
BMC Bioinform., 2018

Device-Free Localization Based on CSI Fingerprints and Deep Neural Networks.
Proceedings of the 15th Annual IEEE International Conference on Sensing, 2018

2017
Predicting HPC parallel program performance based on LLVM compiler.
Clust. Comput., 2017

2016
Communication optimization for RDMA-based science data transmission tools.
J. Supercomput., 2016


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