Pu Zhao

According to our database, Pu Zhao authored at least 53 papers between 2017 and 2024.

Collaborative distances:

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

2024

EdgeQAT: Entropy and Distribution Guided Quantization-Aware Training for the Acceleration of Lightweight LLMs on the Edge.

Xuan Shen, Zhenglun Kong, Changdi Yang, Zhaoyang Han, Lei Lu, Peiyan Dong, Cheng Lyu, Chih-hsiang Li, Xuehang Guo, Zhihao Shu, Wei Niu, Miriam Leeser, Pu Zhao, Yanzhi Wang

CoRR, 2024

Detection and Recovery Against Deep Neural Network Fault Injection Attacks Based on Contrastive Learning.

Chenan Wang, Pu Zhao, Siyue Wang, Xue Lin

CoRR, 2024

2023

The Autonomous Vehicle Assistant (AVA): Emerging technology design supporting blind and visually impaired travelers in autonomous transportation.

Paul D. S. Fink, Stacy A. Doore, Xue Lin, Matthew Maring, Pu Zhao, Aubree Nygaard, Grant Beals, Richard R. Corey, Raymond J. Perry, Katherine Freund, Velin Dimitrov, Nicholas A. Giudice

Int. J. Hum. Comput. Stud., November, 2023

Gaining the Sparse Rewards by Exploring Binary Lottery Tickets in Spiking Neural Network.

Hao Cheng, Jiahang Cao, Erjia Xiao, Pu Zhao, Mengshu Sun, Jiaxu Wang, Jize Zhang, Xue Lin, Bhavya Kailkhura, Kaidi Xu, Renjing Xu

CoRR, 2023

Condense: A Framework for Device and Frequency Adaptive Neural Network Models on the Edge.

Yifan Gong, Pu Zhao, Zheng Zhan, Yushu Wu, Chao Wu, Zhenglun Kong, Minghai Qin, Caiwen Ding, Yanzhi Wang

Proceedings of the 60th ACM/IEEE Design Automation Conference, 2023

Pruning Parameterization with Bi-level Optimization for Efficient Semantic Segmentation on the Edge.

Changdi Yang, Pu Zhao, Yanyu Li, Wei Niu, Jiexiong Guan, Hao Tang, Minghai Qin, Bin Ren, Xue Lin, Yanzhi Wang

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

Towards Real-Time Segmentation on the Edge.

Yanyu Li, Changdi Yang, Pu Zhao, Geng Yuan, Wei Niu, Jiexiong Guan, Hao Tang, Minghai Qin, Qing Jin, Bin Ren, Xue Lin, Yanzhi Wang

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

Less is More: Data Pruning for Faster Adversarial Training.

Yize Li, Pu Zhao, Xue Lin, Bhavya Kailkhura, Ryan A. Goldhahn

Proceedings of the Workshop on Artificial Intelligence Safety 2023 (SafeAI 2023) co-located with the Thirty-Seventh AAAI Conference on Artificial Intelligence (AAAI 2023), 2023

2022

Automatic Mapping of the Best-Suited DNN Pruning Schemes for Real-Time Mobile Acceleration.

Yifan Gong, Geng Yuan, Zheng Zhan, Wei Niu, Zhengang Li, Pu Zhao, Yuxuan Cai, Sijia Liu, Bin Ren, Xue Lin, Xulong Tang, Yanzhi Wang

ACM Trans. Design Autom. Electr. Syst., 2022

Efficient Multi-Prize Lottery Tickets: Enhanced Accuracy, Training, and Inference Speed.

Hao Cheng, Pu Zhao, Yize Li, Xue Lin, James Diffenderfer, Ryan A. Goldhahn, Bhavya Kailkhura

CoRR, 2022

More or Less (MoL): Defending against Multiple Perturbation Attacks on Deep Neural Networks through Model Ensemble and Compression.

Hao Cheng, Kaidi Xu, Zhengang Li, Pu Zhao, Chenan Wang, Xue Lin, Bhavya Kailkhura, Ryan A. Goldhahn

Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision Workshops, 2022

Advancing Model Pruning via Bi-level Optimization.

Yihua Zhang, Yuguang Yao, Parikshit Ram, Pu Zhao, Tianlong Chen, Mingyi Hong, Yanzhi Wang, Sijia Liu

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

BLCR: Towards Real-time DNN Execution with Block-based Reweighted Pruning.

Xiaolong Ma, Geng Yuan, Zhengang Li, Yifan Gong, Tianyun Zhang, Wei Niu, Zheng Zhan, Pu Zhao, Ning Liu, Jian Tang, Xue Lin, Bin Ren, Yanzhi Wang

Proceedings of the 23rd International Symposium on Quality Electronic Design, 2022

Learning to Generate Image Source-Agnostic Universal Adversarial Perturbations.

Pu Zhao, Parikshit Ram, Songtao Lu, Yuguang Yao, Djallel Bouneffouf, Xue Lin, Sijia Liu

Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022

Pruning-as-Search: Efficient Neural Architecture Search via Channel Pruning and Structural Reparameterization.

Yanyu Li, Pu Zhao, Geng Yuan, Xue Lin, Yanzhi Wang, Xin Chen

Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022

All-in-One: A Highly Representative DNN Pruning Framework for Edge Devices with Dynamic Power Management.

Yifan Gong, Zheng Zhan, Pu Zhao, Yushu Wu, Chao Wu, Caiwen Ding, Weiwen Jiang, Minghai Qin, Yanzhi Wang

Proceedings of the 41st IEEE/ACM International Conference on Computer-Aided Design, 2022

Compiler-Aware Neural Architecture Search for On-Mobile Real-time Super-Resolution.

Yushu Wu, Yifan Gong, Pu Zhao, Yanyu Li, Zheng Zhan, Wei Niu, Hao Tang, Minghai Qin, Bin Ren, Yanzhi Wang

Proceedings of the Computer Vision - ECCV 2022, 2022

2021

Achieving Real-Time Object Detection on MobileDevices with Neural Pruning Search.

Pu Zhao, Wei Niu, Geng Yuan, Yuxuan Cai, Bin Ren, Yanzhi Wang, Xue Lin

CoRR, 2021

High-Robustness, Low-Transferability Fingerprinting of Neural Networks.

Siyue Wang, Xiao Wang, Pin-Yu Chen, Pu Zhao, Xue Lin

CoRR, 2021

CoCoPIE: enabling real-time AI on off-the-shelf mobile devices via compression-compilation co-design.

Hui Guan, Shaoshan Liu, Xiaolong Ma, Wei Niu, Bin Ren, Xipeng Shen, Yanzhi Wang, Pu Zhao

Commun. ACM, 2021

Brief Industry Paper: Towards Real-Time 3D Object Detection for Autonomous Vehicles with Pruning Search.

Pu Zhao, Wei Niu, Geng Yuan, Yuxuan Cai, Hsin-Hsuan Sung, Shaoshan Liu, Sijia Liu, Xipeng Shen, Bin Ren, Yanzhi Wang, Xue Lin

Proceedings of the 27th IEEE Real-Time and Embedded Technology and Applications Symposium, 2021

Characteristic Examples: High-Robustness, Low-Transferability Fingerprinting of Neural Networks.

Siyue Wang, Xiao Wang, Pin-Yu Chen, Pu Zhao, Xue Lin

Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021

A Compression-Compilation Framework for On-mobile Real-time BERT Applications.

Wei Niu, Zhenglun Kong, Geng Yuan, Weiwen Jiang, Jiexiong Guan, Caiwen Ding, Pu Zhao, Sijia Liu, Bin Ren, Yanzhi Wang

Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021

Achieving on-Mobile Real-Time Super-Resolution with Neural Architecture and Pruning Search.

Zheng Zhan, Yifan Gong, Pu Zhao, Geng Yuan, Wei Niu, Yushu Wu, Tianyun Zhang, Malith Jayaweera, David R. Kaeli, Bin Ren, Xue Lin, Yanzhi Wang

Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

Neural Pruning Search for Real-Time Object Detection of Autonomous Vehicles.

Pu Zhao, Geng Yuan, Yuxuan Cai, Wei Niu, Qi Liu, Wujie Wen, Bin Ren, Yanzhi Wang, Xue Lin

Proceedings of the 58th ACM/IEEE Design Automation Conference, 2021

NPAS: A Compiler-Aware Framework of Unified Network Pruning and Architecture Search for Beyond Real-Time Mobile Acceleration.

Zhengang Li, Geng Yuan, Wei Niu, Pu Zhao, Yanyu Li, Yuxuan Cai, Xuan Shen, Zheng Zhan, Zhenglun Kong, Qing Jin, Zhiyu Chen, Sijia Liu, Kaiyuan Yang, Bin Ren, Yanzhi Wang, Xue Lin

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

Intrinsic Examples: Robust Fingerprinting of Deep Neural Networks.

Siyue Wang, Pu Zhao, Xiao Wang, Sang Chin, Thomas Wahl, Yunsi Fei, Qi Alfred Chen, Xue Lin

Proceedings of the 32nd British Machine Vision Conference 2021, 2021

2020

Exploring GPU acceleration of Deep Neural Networks using Block Circulant Matrices.

Shi Dong, Pu Zhao, Xue Lin, David R. Kaeli

Parallel Comput., 2020

Achieving Real-Time LiDAR 3D Object Detection on a Mobile Device.

Pu Zhao, Wei Niu, Geng Yuan, Yuxuan Cai, Hsin-Hsuan Sung, Wujie Wen, Sijia Liu, Xipeng Shen, Bin Ren, Yanzhi Wang, Xue Lin

CoRR, 2020

6.7ms on Mobile with over 78% ImageNet Accuracy: Unified Network Pruning and Architecture Search for Beyond Real-Time Mobile Acceleration.

Zhengang Li, Geng Yuan, Wei Niu, Yanyu Li, Pu Zhao, Yuxuan Cai, Xuan Shen, Zheng Zhan, Zhenglun Kong, Qing Jin, Zhiyu Chen, Sijia Liu, Kaiyuan Yang, Bin Ren, Yanzhi Wang, Xue Lin

CoRR, 2020

Learned Fine-Tuner for Incongruous Few-Shot Learning.

Pu Zhao, Sijia Liu, Parikshit Ram, Songtao Lu, Djallel Bouneffouf, Xue Lin

CoRR, 2020

Achieving Real-Time Execution of Transformer-based Large-scale Models on Mobile with Compiler-aware Neural Architecture Optimization.

Wei Niu, Zhenglun Kong, Geng Yuan, Weiwen Jiang, Jiexiong Guan, Caiwen Ding, Pu Zhao, Sijia Liu, Bin Ren, Yanzhi Wang

CoRR, 2020

A Privacy-Preserving DNN Pruning and Mobile Acceleration Framework.

Zheng Zhan, Yifan Gong, Zhengang Li, Pu Zhao, Xiaolong Ma, Wei Niu, Xiaolin Xu, Bin Ren, Yanzhi Wang, Xue Lin

CoRR, 2020

Defending against Backdoor Attack on Deep Neural Networks.

Hao Cheng, Kaidi Xu, Sijia Liu, Pin-Yu Chen, Pu Zhao, Xue Lin

CoRR, 2020

BLK-REW: A Unified Block-based DNN Pruning Framework using Reweighted Regularization Method.

Xiaolong Ma, Zhengang Li, Yifan Gong, Tianyun Zhang, Wei Niu, Zheng Zhan, Pu Zhao, Jian Tang, Xue Lin, Bin Ren, Yanzhi Wang

CoRR, 2020

Towards Real-Time DNN Inference on Mobile Platforms with Model Pruning and Compiler Optimization.

Wei Niu, Pu Zhao, Zheng Zhan, Xue Lin, Yanzhi Wang, Bin Ren

Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020

Bridging Mode Connectivity in Loss Landscapes and Adversarial Robustness.

Pu Zhao, Pin-Yu Chen, Payel Das, Karthikeyan Natesan Ramamurthy, Xue Lin

Proceedings of the 8th International Conference on Learning Representations, 2020

3D CNN Acceleration on FPGA using Hardware-Aware Pruning.

Mengshu Sun, Pu Zhao, Mehmet Güngör, Massoud Pedram, Miriam Leeser, Xue Lin

Proceedings of the 57th ACM/IEEE Design Automation Conference, 2020

Towards Query-Efficient Black-Box Adversary with Zeroth-Order Natural Gradient Descent.

Pu Zhao, Pin-Yu Chen, Siyue Wang, Xue Lin

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

Towards Certificated Model Robustness Against Weight Perturbations.

Tsui-Wei Weng, Pu Zhao, Sijia Liu, Pin-Yu Chen, Xue Lin, Luca Daniel

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019

Interpreting Adversarial Examples by Activation Promotion and Suppression.

Kaidi Xu, Sijia Liu, Gaoyuan Zhang, Mengshu Sun, Pu Zhao, Quanfu Fan, Chuang Gan, Xue Lin

CoRR, 2019

Structured Adversarial Attack: Towards General Implementation and Better Interpretability.

Kaidi Xu, Sijia Liu, Pu Zhao, Pin-Yu Chen, Huan Zhang, Quanfu Fan, Deniz Erdogmus, Yanzhi Wang, Xue Lin

Proceedings of the 7th International Conference on Learning Representations, 2019

On the Design of Black-Box Adversarial Examples by Leveraging Gradient-Free Optimization and Operator Splitting Method.

Pu Zhao, Sijia Liu, Pin-Yu Chen, Nghia Hoang, Kaidi Xu, Bhavya Kailkhura, Xue Lin

Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision, 2019

HSIM-DNN: Hardware Simulator for Computation-, Storage- and Power-Efficient Deep Neural Networks.

Mengshu Sun, Pu Zhao, Yanzhi Wang, Naehyuck Chang, Xue Lin

Proceedings of the 2019 on Great Lakes Symposium on VLSI, 2019

Fault Sneaking Attack: a Stealthy Framework for Misleading Deep Neural Networks.

Pu Zhao, Siyue Wang, Cheng Gongye, Yanzhi Wang, Yunsi Fei, Xue Lin

Proceedings of the 56th Annual Design Automation Conference 2019, 2019

ADMM attack: an enhanced adversarial attack for deep neural networks with undetectable distortions.

Pu Zhao, Kaidi Xu, Sijia Liu, Yanzhi Wang, Xue Lin

Proceedings of the 24th Asia and South Pacific Design Automation Conference, 2019

2018

Structured Adversarial Attack: Towards General Implementation and Better Interpretability.

Kaidi Xu, Sijia Liu, Pu Zhao, Pin-Yu Chen, Huan Zhang, Deniz Erdogmus, Yanzhi Wang, Xue Lin

CoRR, 2018

An ADMM-Based Universal Framework for Adversarial Attacks on Deep Neural Networks.

Pu Zhao, Sijia Liu, Yanzhi Wang, Xue Lin

Proceedings of the 2018 ACM Multimedia Conference on Multimedia Conference, 2018

Defensive dropout for hardening deep neural networks under adversarial attacks.

Siyue Wang, Xiao Wang, Pu Zhao, Wujie Wen, David R. Kaeli, Peter Chin, Xue Lin

Proceedings of the International Conference on Computer-Aided Design, 2018

Reinforced Adversarial Attacks on Deep Neural Networks Using ADMM.

Pu Zhao, Kaidi Xu, Tianyun Zhang, Makan Fardad, Yanzhi Wang, Xue Lin

Proceedings of the 2018 IEEE Global Conference on Signal and Information Processing, 2018

Defending DNN Adversarial Attacks with Pruning and Logits Augmentation.

Siyue Wang, Xiao Wang, Shaokai Ye, Pu Zhao, Xue Lin

Proceedings of the 2018 IEEE Global Conference on Signal and Information Processing, 2018

A deep reinforcement learning framework for optimizing fuel economy of hybrid electric vehicles.

Pu Zhao, Yanzhi Wang, Naehyuck Chang, Qi Zhu, Xue Lin

Proceedings of the 23rd Asia and South Pacific Design Automation Conference, 2018

2017

Hierarchical resource allocation and consolidation framework in a multi-core server cluster using a Markov decision process model.

Pu Zhao, Xue Lin, Yanzhi Wang, Shuang Chen, Massoud Pedram

IET Cyper-Phys. Syst.: Theory & Appl., 2017