Yongqin Wang

According to our database, Yongqin Wang authored at least 27 papers between 2018 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2025

Harnessing the potential of social media platforms for sustainable and inclusive learning among older adults in the digital era.

Yongqin Wang, Ping Huang

Interact. Learn. Environ., September, 2025

Characterization of GPU TEE Overheads in Distributed Data Parallel ML Training.

Jonghytun Lee, Yongqin Wang, Rachit Rajat, Murali Annavaram

CoRR, January, 2025

PIGEON: A High Throughput Framework for Private Inference of Neural Networks using Secure Multiparty Computation.

Christopher Harth-Kitzerow, Yongqin Wang, Rachit Rajat, Georg Carle, Murali Annavaram

Proc. Priv. Enhancing Technol., 2025

High-Throughput Secure Multiparty Computation with an Honest Majority in Various Network Settings.

Christopher Harth-Kitzerow, Ajith Suresh, Yongqin Wang, Hossein Yalame, Georg Carle, Murali Annavaram

Proc. Priv. Enhancing Technol., 2025

External validation and application of risk prediction model for ventilator-associated pneumonia in ICU patients with mechanical ventilation: A prospective cohort study.

Jiaying Li, Guifang Li, Ziqing Liu, Jincong Wang, Xueping Jia, Hongxiao Yang, Yongqin Wang

Int. J. Medical Informatics, 2025

2024

PIGEON: A Framework for Private Inference of Neural Networks.

Christopher Harth-Kitzerow, Yongqin Wang, Rachit Rajat, Georg Carle, Murali Annavaram

IACR Cryptol. ePrint Arch., 2024

Fastrack: Fast IO for Secure ML using GPU TEEs.

Yongqin Wang, Rachit Rajat, Jonghyun Lee, Tingting Tang, Murali Annavaram

CoRR, 2024

MPC-Pipe: an Efficient Pipeline Scheme for Semi-honest MPC Machine Learning.

Yongqin Wang, Rachit Rajat, Murali Annavaram

Proceedings of the 29th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, 2024

2023

CompactTag: Minimizing Computation Overheads in Actively-Secure MPC for Deep Neural Networks.

Yongqin Wang, Pratik Sarkar, Nishat Koti, Arpita Patra, Murali Annavaram

IACR Cryptol. ePrint Arch., 2023

LAORAM: A Look Ahead ORAM Architecture for Training Large Embedding Tables.

Rachit Rajat, Yongqin Wang, Murali Annavaram

Proceedings of the 50th Annual International Symposium on Computer Architecture, 2023

2022

MPC-Pipe: an Efficient Pipeline Scheme for Secure Multi-party Machine Learning Inference.

Yongqin Wang, Rachit Rajat, Murali Annavaram

CoRR, 2022

PageORAM: An Efficient DRAM Page Aware ORAM Strategy.

Rachit Rajat, Yongqin Wang, Murali Annavaram

Proceedings of the 55th IEEE/ACM International Symposium on Microarchitecture, 2022

Characterization of MPC-based Private Inference for Transformer-based Models.

Yongqin Wang, G. Edward Suh, Wenjie Xiong, Benjamin Lefaudeux, Brian Knott, Murali Annavaram, Hsien-Hsin S. Lee

Proceedings of the International IEEE Symposium on Performance Analysis of Systems and Software, 2022

2021

Look Ahead ORAM: Obfuscating Addresses in Recommendation Model Training.

Rachit Rajat, Yongqin Wang, Murali Annavaram

CoRR, 2021

Byzantine-Robust and Privacy-Preserving Framework for FedML.

Hanieh Hashemi, Yongqin Wang, Chuan Guo, Murali Annavaram

CoRR, 2021

Privacy and Integrity Preserving Training Using Trusted Hardware.

Hanieh Hashemi, Yongqin Wang, Murali Annavaram

CoRR, 2021

DarKnight: An Accelerated Framework for Privacy and Integrity Preserving Deep Learning Using Trusted Hardware.

Hanieh Hashemi, Yongqin Wang, Murali Annavaram

Proceedings of the MICRO '21: 54th Annual IEEE/ACM International Symposium on Microarchitecture, 2021

Research on Evaluation Model of College English Online and Offline Mixed Learning Under Digital Environment.

Yongqin Wang

Proceedings of the Design, Learning, and Innovation - 6th EAI International Conference, 2021

Origami Inference: Private Inference Using Hardware Enclaves.

Krishna Giri Narra, Zhifeng Lin, Yongqin Wang, Keshav Balasubramanian, Murali Annavaram

Proceedings of the 14th IEEE International Conference on Cloud Computing, 2021

2020

Research on meta-action decomposition and meta-action unit modeling technology for electromechanical product.

Yulong Li, Xiaogang Zhang, Yan Ran, Genbao Zhang, Yongqin Wang

Qual. Reliab. Eng. Int., 2020

A reliability-based fatigue design for mechanical components under material variability.

Weiqi Du, Yongqin Wang, Yuanxin Luo

Qual. Reliab. Eng. Int., 2020

DarKnight: A Data Privacy Scheme for Training and Inference of Deep Neural Networks.

Hanieh Hashemi, Yongqin Wang, Murali Annavaram

CoRR, 2020

2019

Time-variant reliability analysis using the parallel subset simulation.

Weiqi Du, Yuanxin Luo, Yongqin Wang

Reliab. Eng. Syst. Saf., 2019

Research on reliability allocation technology for NC machine tool meta-action.

Yulong Li, Genbao Zhang, Yongqin Wang, Xiaogang Zhang, Yan Ran

Qual. Reliab. Eng. Int., 2019

A general framework for fatigue reliability analysis of a high temperature component.

Weiqi Du, Yuanxin Luo, Yongqin Wang, Ling Ma

Qual. Reliab. Eng. Int., 2019

Privacy-Preserving Inference in Machine Learning Services Using Trusted Execution Environments.

Krishna Giri Narra, Zhifeng Lin, Yongqin Wang, Keshav Balasubramaniam, Murali Annavaram

CoRR, 2019

2018

Teaching Effect of College English Based on Cloud Class Platform.

Yongqin Wang, Mingming Han, Fei Lang

Proceedings of the e-Learning, e-Education, and Online Training, 2018