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ORCIDShanglin Zhou
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2020 – today
- 2024
[j6]Songyang Han
, Shanglin Zhou, Jiangwei Wang, Lynn Pepin, Caiwen Ding, Jie Fu, Fei Miao:
A Multi-Agent Reinforcement Learning Approach for Safe and Efficient Behavior Planning of Connected Autonomous Vehicles. IEEE Trans. Intell. Transp. Syst. 25(5): 3654-3670 (2024)- 2023
- [j5]Shanglin Zhou, Mikhail A. Bragin, Deniz Gurevin, Lynn Pepin, Fei Miao, Caiwen Ding:
Surrogate Lagrangian Relaxation: A Path to Retrain-Free Deep Neural Network Pruning. ACM Trans. Design Autom. Electr. Syst. 28(6): 102:1-102:19 (2023) - [c16]Hongwu Peng, Shanglin Zhou, Yukui Luo, Nuo Xu, Shijin Duan, Ran Ran, Jiahui Zhao, Chenghong Wang, Tong Geng, Wujie Wen, Xiaolin Xu, Caiwen Ding:
PASNet: Polynomial Architecture Search Framework for Two-party Computation-based Secure Neural Network Deployment. DAC 2023: 1-6 - [c15]Shanglin Zhou, Yingjie Li, Minhan Lou, Weilu Gao, Zhijie Shi, Cunxi Yu, Caiwen Ding:
Physics-aware Roughness Optimization for Diffractive Optical Neural Networks. DAC 2023: 1-6 - [c14]Ya-sine Agrignan, Shanglin Zhou, Jun Bai, Sahidul Islam, Sheida Nabavi, Mimi Xie, Caiwen Ding:
A Deep Learning Approach for Ventricular Arrhythmias Classification using Microcontroller. ISQED 2023: 1-5 - [i12]Hongwu Peng, Shanglin Zhou, Yukui Luo, Nuo Xu, Shijin Duan, Ran Ran, Jiahui Zhao, Shaoyi Huang, Xi Xie, Chenghong Wang, Tong Geng, Wujie Wen, Xiaolin Xu, Caiwen Ding:
RRNet: Towards ReLU-Reduced Neural Network for Two-party Computation Based Private Inference. CoRR abs/2302.02292 (2023) - [i11]Songyang Han, Shanglin Zhou, Lynn Pepin, Jiangwei Wang, Caiwen Ding, Fei Miao:
Shared Information-Based Safe And Efficient Behavior Planning For Connected Autonomous Vehicles. CoRR abs/2302.04321 (2023) - [i10]Shanglin Zhou, Yingjie Li, Minhan Lou, Weilu Gao, Zhijie Shi, Cunxi Yu, Caiwen Ding:
Physics-aware Roughness Optimization for Diffractive Optical Neural Networks. CoRR abs/2304.01500 (2023) - [i9]Shanglin Zhou, Mikhail A. Bragin, Lynn Pepin, Deniz Gurevin, Fei Miao, Caiwen Ding:
Surrogate Lagrangian Relaxation: A Path To Retrain-free Deep Neural Network Pruning. CoRR abs/2304.04120 (2023) - [i8]Hongwu Peng, Shanglin Zhou, Yukui Luo, Nuo Xu, Shijin Duan, Ran Ran, Jiahui Zhao, Chenghong Wang, Tong Geng, Wujie Wen, Xiaolin Xu, Caiwen Ding:
PASNet: Polynomial Architecture Search Framework for Two-party Computation-based Secure Neural Network Deployment. CoRR abs/2306.15513 (2023) - 2022
- [j4]Shanglin Zhou, Xiaowei Xu, Jun Bai, Mikhail A. Bragin:
Combining multi-view ensemble and surrogate lagrangian relaxation for real-time 3D biomedical image segmentation on the edge. Neurocomputing 512: 466-481 (2022) - [j3]Shanglin Zhou, Sotiris C. Masmanidis, Dean V. Buonomano:
Encoding time in neural dynamic regimes with distinct computational tradeoffs. PLoS Comput. Biol. 18(3) (2022) - [c13]Bingyu Liu, Rujia Wang, Zhongjie Ba, Shanglin Zhou, Caiwen Ding, Yuan Hong:
Poster: Cryptographic Inferences for Video Deep Neural Networks. CCS 2022: 3395-3397 - [c12]Sahidul Islam, Jieren Deng, Shanglin Zhou, Chen Pan, Caiwen Ding, Mimi Xie:
Enabling Fast Deep Learning on Tiny Energy-Harvesting IoT Devices. DATE 2022: 921-926 - [c11]Sahidul Islam, Shanglin Zhou, Ran Ran, Yufang Jin, Wujie Wen, Caiwen Ding, Mimi Xie:
EVE: Environmental Adaptive Neural Network Models for Low-Power Energy Harvesting System. ICCAD 2022: 35:1-35:9 - [c10]Zhirui Hu, Jinyang Li, Zhenyu Pan, Shanglin Zhou, Lei Yang, Caiwen Ding, Omer Khan, Tong Geng, Weiwen Jiang:
On the Design of Quantum Graph Convolutional Neural Network in the NISQ-Era and Beyond. ICCD 2022: 290-297 - [c9]Wei Wei, Sahidul Islam, Jishnu Banerjee, Shanglin Zhou, Chen Pan, Caiwen Ding, Mimi Xie:
An Intermittent OTA Approach to Update the DL Weights on Energy Harvesting Devices. ISQED 2022: 1-6 - [i7]Sahidul Islam, Shanglin Zhou, Ran Ran, Yufang Jin, Wujie Wen, Caiwen Ding, Mimi Xie:
EVE: Environmental Adaptive Neural Network Models for Low-power Energy Harvesting System. CoRR abs/2207.09258 (2022) - 2021
- [j2]Shanglin Zhou, Paolo Braca, Stefano Maranò, Peter Willett, Leonardo Maria Millefiori, Domenico Gaglione, Krishna R. Pattipati:
Application of Hidden Markov Models to Analyze, Group and Visualize Spatio-Temporal COVID-19 Data. IEEE Access 9: 134384-134401 (2021) - [c8]Hongwu Peng, Shanglin Zhou, Scott Weitze, Jiaxin Li, Sahidul Islam, Tong Geng, Ang Li, Wei Zhang, Minghu Song, Mimi Xie, Hang Liu, Caiwen Ding:
Binary Complex Neural Network Acceleration on FPGA : (Invited Paper). ASAP 2021: 85-92 - [c7]Tianyun Zhang, Xiaolong Ma, Zheng Zhan, Shanglin Zhou, Caiwen Ding, Makan Fardad, Yanzhi Wang:
A Unified DNN Weight Pruning Framework Using Reweighted Optimization Methods. DAC 2021: 493-498 - [c6]Zhepeng Wang, Zhiding Liang, Shanglin Zhou, Caiwen Ding, Yiyu Shi, Weiwen Jiang:
Exploration of Quantum Neural Architecture by Mixing Quantum Neuron Designs: (Invited Paper). ICCAD 2021: 1-7 - [c5]Deniz Gurevin, Mikhail A. Bragin, Caiwen Ding, Shanglin Zhou, Lynn Pepin, Bingbing Li, Fei Miao:
Enabling Retrain-free Deep Neural Network Pruning Using Surrogate Lagrangian Relaxation. IJCAI 2021: 2497-2504 - [c4]Yijue Wang, Chenghong Wang, Zigeng Wang, Shanglin Zhou, Hang Liu, Jinbo Bi, Caiwen Ding, Sanguthevar Rajasekaran:
Against Membership Inference Attack: Pruning is All You Need. IJCAI 2021: 3141-3147 - [c3]Shanglin Zhou, Mimi Xie, Yufang Jin, Fei Miao, Caiwen Ding:
An End-to-end Multi-task Object Detection using Embedded GPU in Autonomous Driving. ISQED 2021: 122-128 - [i6]Hongwu Peng, Shanglin Zhou, Scott Weitze, Jiaxin Li, Sahidul Islam, Tong Geng, Ang Li, Wei Zhang, Minghu Song, Mimi Xie, Hang Liu, Caiwen Ding:
Binary Complex Neural Network Acceleration on FPGA. CoRR abs/2108.04811 (2021) - [i5]Zhepeng Wang, Zhiding Liang, Shanglin Zhou, Caiwen Ding, Jinjun Xiong, Yiyu Shi, Weiwen Jiang:
Exploration of Quantum Neural Architecture by Mixing Quantum Neuron Designs. CoRR abs/2109.03806 (2021) - [i4]Sahidul Islam, Jieren Deng, Shanglin Zhou, Chen Pan, Caiwen Ding, Mimi Xie:
Enabling Super-Fast Deep Learning on Tiny Energy-Harvesting IoT Devices. CoRR abs/2111.14051 (2021) - 2020
- [c2]Shanglin Zhou, Bingbing Li, Caiwu Ding, Lu Lu, Caiwen Ding:
An Efficient Deep Reinforcement Learning Framework for UAVs. ISQED 2020: 323-328 - [i3]Tianyun Zhang, Xiaolong Ma, Zheng Zhan, Shanglin Zhou, Minghai Qin, Fei Sun, Yen-Kuang Chen, Caiwen Ding, Makan Fardad, Yanzhi Wang:
A Unified DNN Weight Compression Framework Using Reweighted Optimization Methods. CoRR abs/2004.05531 (2020) - [i2]Yijue Wang, Chenghong Wang, Zigeng Wang, Shanglin Zhou, Hang Liu, Jinbo Bi, Caiwen Ding, Sanguthevar Rajasekaran:
MCMIA: Model Compression Against Membership Inference Attack in Deep Neural Networks. CoRR abs/2008.13578 (2020) - [i1]Deniz Gurevin, Shanglin Zhou, Lynn Pepin, Bingbing Li, Mikhail A. Bragin, Caiwen Ding, Fei Miao:
A Surrogate Lagrangian Relaxation-based Model Compression for Deep Neural Networks. CoRR abs/2012.10079 (2020)
2010 – 2019
- 2018
- [c1]Xingyu Cai, Shanglin Zhou, Sanguthevar Rajasekaran:
JUMP: A Fast Deterministic Algorithm to Find the Closest Pair of Subsequences. SDM 2018: 73-80 - 2013
- [j1]Lili Xu, Shanglin Zhou, Kunqian Yu, Bo Gao, Hualiang Jiang, Xuechu Zhen, Wei Fu:
Molecular Modeling of the 3D Structure of 5-HT1AR: Discovery of Novel 5-HT1AR Agonists via Dynamic Pharmacophore-Based Virtual Screening. J. Chem. Inf. Model. 53(12): 3202-3211 (2013)
Coauthor Index
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last updated on 2024-11-08 20:33 CET by the dblp team
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