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2020 – today
- 2024
[i10]Christopher Harth-Kitzerow, Yongqin Wang, Rachit Rajat, Georg Carle, Murali Annavaram:
PIGEON: A Framework for Private Inference of Neural Networks. IACR Cryptol. ePrint Arch. 2024: 1371 (2024)- 2023
- [c7]Rachit Rajat
, Yongqin Wang, Murali Annavaram:
LAORAM: A Look Ahead ORAM Architecture for Training Large Embedding Tables. ISCA 2023: 76:1-76:15 - [i9]Yongqin Wang, Pratik Sarkar, Nishat Koti, Arpita Patra, Murali Annavaram:
CompactTag: Minimizing Computation Overheads in Actively-Secure MPC for Deep Neural Networks. CoRR abs/2311.04406 (2023) - [i8]Yongqin Wang, Pratik Sarkar, Nishat Koti, Arpita Patra, Murali Annavaram:
CompactTag: Minimizing Computation Overheads in Actively-Secure MPC for Deep Neural Networks. IACR Cryptol. ePrint Arch. 2023: 1729 (2023) - 2022
- [c6]Yongqin Wang, G. Edward Suh, Wenjie Xiong, Benjamin Lefaudeux, Brian Knott, Murali Annavaram, Hsien-Hsin S. Lee:
Characterization of MPC-based Private Inference for Transformer-based Models. ISPASS 2022: 187-197 - [c5]Rachit Rajat, Yongqin Wang, Murali Annavaram:
PageORAM: An Efficient DRAM Page Aware ORAM Strategy. MICRO 2022: 91-107 - [i7]Hanieh Hashemi, Yongqin Wang, Murali Annavaram:
DarKnight: An Accelerated Framework for Privacy and Integrity Preserving Deep Learning Using Trusted Hardware. CoRR abs/2207.00083 (2022) - [i6]Yongqin Wang, Rachit Rajat, Murali Annavaram:
MPC-Pipe: an Efficient Pipeline Scheme for Secure Multi-party Machine Learning Inference. CoRR abs/2209.13643 (2022) - 2021
- [c4]Krishna Giri Narra, Zhifeng Lin, Yongqin Wang, Keshav Balasubramanian, Murali Annavaram:
Origami Inference: Private Inference Using Hardware Enclaves. CLOUD 2021: 78-84 - [c3]Yongqin Wang:
Research on Evaluation Model of College English Online and Offline Mixed Learning Under Digital Environment. DLI 2021: 71-76 - [c2]Hanieh Hashemi, Yongqin Wang, Murali Annavaram:
DarKnight: An Accelerated Framework for Privacy and Integrity Preserving Deep Learning Using Trusted Hardware. MICRO 2021: 212-224 - [i5]Hanieh Hashemi, Yongqin Wang, Murali Annavaram:
Privacy and Integrity Preserving Training Using Trusted Hardware. CoRR abs/2105.00334 (2021) - [i4]Hanieh Hashemi, Yongqin Wang, Chuan Guo, Murali Annavaram:
Byzantine-Robust and Privacy-Preserving Framework for FedML. CoRR abs/2105.02295 (2021) - [i3]Rachit Rajat, Yongqin Wang, Murali Annavaram:
Look Ahead ORAM: Obfuscating Addresses in Recommendation Model Training. CoRR abs/2107.08094 (2021) - 2020
- [j5]Yulong Li, Xiaogang Zhang, Yan Ran, Genbao Zhang, Yongqin Wang:
Research on meta-action decomposition and meta-action unit modeling technology for electromechanical product. Qual. Reliab. Eng. Int. 36(1): 268-284 (2020) - [j4]Weiqi Du, Yongqin Wang, Yuanxin Luo:
A reliability-based fatigue design for mechanical components under material variability. Qual. Reliab. Eng. Int. 36(1): 388-402 (2020) - [i2]Hanieh Hashemi, Yongqin Wang, Murali Annavaram:
DarKnight: A Data Privacy Scheme for Training and Inference of Deep Neural Networks. CoRR abs/2006.01300 (2020)
2010 – 2019
- 2019
- [j3]Weiqi Du, Yuanxin Luo, Yongqin Wang, Ling Ma:
A general framework for fatigue reliability analysis of a high temperature component. Qual. Reliab. Eng. Int. 35(1): 292-303 (2019) - [j2]Yulong Li, Genbao Zhang, Yongqin Wang, Xiaogang Zhang, Yan Ran:
Research on reliability allocation technology for NC machine tool meta-action. Qual. Reliab. Eng. Int. 35(6): 2016-2044 (2019) - [j1]Weiqi Du, Yuanxin Luo, Yongqin Wang:
Time-variant reliability analysis using the parallel subset simulation. Reliab. Eng. Syst. Saf. 182: 250-257 (2019) - [i1]Krishna Giri Narra, Zhifeng Lin, Yongqin Wang, Keshav Balasubramaniam, Murali Annavaram:
Privacy-Preserving Inference in Machine Learning Services Using Trusted Execution Environments. CoRR abs/1912.03485 (2019) - 2018
- [c1]Yongqin Wang, Mingming Han, Fei Lang:
Teaching Effect of College English Based on Cloud Class Platform. eLEOT 2018: 27-32
Coauthor Index
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