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2020 – today
- 2024
[j2]Wangshu Liu, Ye Yue, Xiang Chen
, Qing Gu, Pengzhan Zhao, Xuejun Liu, Jianjun Zhao:
SeDPGK: Semi-supervised software defect prediction with graph representation learning and knowledge distillation. Inf. Softw. Technol. 174: 107510 (2024)- [c11]Xiaoyu Guo, Jianjun Zhao, Pengzhan Zhao:
On Repairing Quantum Programs Using ChatGPT. Q-SE@ICSE 2024: 9-16 - [c10]Shan Yu, Zhenting Zhu, Yu Chen, Hanchen Xu, Pengzhan Zhao, Yang Wang, Arthi Padmanabhan, Hugo Latapie, Harry Xu:
VQPy: An Object-Oriented Approach to Modern Video Analytics. MLSys 2024 - [i10]Xiaoyu Guo, Jianjun Zhao, Pengzhan Zhao:
On Repairing Quantum Programs Using ChatGPT. CoRR abs/2401.14913 (2024) - 2023
- [j1]Pengzhan Zhao, Zhongtao Miao, Shuhan Lan, Jianjun Zhao:
Bugs4Q: A benchmark of existing bugs to enable controlled testing and debugging studies for quantum programs. J. Syst. Softw. 205: 111805 (2023) - [c9]Pengzhan Zhao, Xiongfei Wu, Zhuo Li, Jianjun Zhao:
QChecker: Detecting Bugs in Quantum Programs via Static Analysis. Q-SE@ICSE 2023: 50-57 - [c8]John Thorpe, Pengzhan Zhao, Jonathan Eyolfson, Yifan Qiao, Zhihao Jia, Minjia Zhang, Ravi Netravali, Guoqing Harry Xu:
Bamboo: Making Preemptible Instances Resilient for Affordable Training of Large DNNs. NSDI 2023: 497-513 - [c7]Pengzhan Zhao, Xiongfei Wu, Junjie Luo, Zhuo Li, Jianjun Zhao:
An Empirical Study of Bugs in Quantum Machine Learning Frameworks. QSW 2023: 68-75 - [d1]Pengzhan Zhao, Zhongtao Miao, Shuhan Lan, Jianjun Zhao:
Bugs4Q: A Benchmark of Existing Bugs to Enable Controlled Testing and Debugging Studies for Quantum Programs. Zenodo, 2023
- [i9]Pengzhan Zhao, Xiongfei Wu, Zhuo Li, Jianjun Zhao:
QChecker: Detecting Bugs in Quantum Programs via Static Analysis. CoRR abs/2304.04387 (2023) - [i8]Pengzhan Zhao, Xiongfei Wu, Junjie Luo, Zhuo Li, Jianjun Zhao:
An Empirical Study of Bugs in Quantum Machine Learning Frameworks. CoRR abs/2306.06369 (2023) - [i7]Shan Yu, Zhenting Zhu, Yu Chen, Hanchen Xu, Pengzhan Zhao, Yang Wang, Arthi Padmanabhan, Hugo Latapie, Harry Xu:
VQPy: An Object-Oriented Approach to Modern Video Analytics. CoRR abs/2311.01623 (2023) - 2022
- [c6]Zhen Zheng, Xuanda Yang, Pengzhan Zhao, Guoping Long, Kai Zhu, Feiwen Zhu, Wenyi Zhao, Xiaoyong Liu, Jun Yang, Jidong Zhai, Shuaiwen Leon Song, Wei Lin:
AStitch: enabling a new multi-dimensional optimization space for memory-intensive ML training and inference on modern SIMT architectures. ASPLOS 2022: 359-373 - [c5]Junjie Luo, Pengzhan Zhao, Zhongtao Miao, Shuhan Lan, Jianjun Zhao:
A Comprehensive Study of Bug Fixes in Quantum Programs. SANER 2022: 1239-1246 - [i6]Junjie Luo, Pengzhan Zhao, Zhongtao Miao, Shuhan Lan, Jianjun Zhao:
A Comprehensive Study of Bug Fixes in Quantum Programs. CoRR abs/2201.08662 (2022) - [i5]John Thorpe, Pengzhan Zhao, Jonathan Eyolfson, Yifan Qiao, Zhihao Jia, Minjia Zhang, Ravi Netravali, Guoqing Harry Xu:
Bamboo: Making Preemptible Instances Resilient for Affordable Training of Large DNNs. CoRR abs/2204.12013 (2022) - 2021
- [c4]Kai Zhu, Wenyi Zhao, Zhen Zheng, Tianyou Guo, Pengzhan Zhao, Junjie Bai, Jun Yang, Xiaoyong Liu, Lansong Diao, Wei Lin:
DISC: A Dynamic Shape Compiler for Machine Learning Workloads. EuroMLSys@EuroSys 2021: 89-95 - [c3]Pengzhan Zhao, Jianjun Zhao, Lei Ma:
Identifying Bug Patterns in Quantum Programs. Q-SE@ICSE 2021: 16-21 - [c2]Pengzhan Zhao, Jianjun Zhao, Zhongtao Miao, Shuhan Lan:
Bugs4Q: A Benchmark of Real Bugs for Quantum Programs. ASE 2021: 1373-1376 - [i4]Kai Zhu, Wenyi Zhao, Zhen Zheng, Tianyou Guo, Pengzhan Zhao, Junjie Bai, Jun Yang, Xiaoyong Liu, Lansong Diao, Wei Lin:
DISC: A Dynamic Shape Compiler for Machine Learning Workloads. CoRR abs/2103.05288 (2021) - [i3]Pengzhan Zhao, Jianjun Zhao, Lei Ma:
Identifying Bug Patterns in Quantum Programs. CoRR abs/2103.09069 (2021) - [i2]Pengzhan Zhao, Jianjun Zhao, Zhongtao Miao, Shuhan Lan:
Bugs4Q: A Benchmark of Real Bugs for Quantum Programs. CoRR abs/2108.09744 (2021) - 2020
- [c1]Yuanqi Li, Arthi Padmanabhan, Pengzhan Zhao, Yufei Wang, Guoqing Harry Xu, Ravi Netravali:
Reducto: On-Camera Filtering for Resource-Efficient Real-Time Video Analytics. SIGCOMM 2020: 359-376 - [i1]Zhen Zheng, Pengzhan Zhao, Guoping Long, Feiwen Zhu, Kai Zhu, Wenyi Zhao, Lansong Diao, Jun Yang, Wei Lin:
FusionStitching: Boosting Memory Intensive Computations for Deep Learning Workloads. CoRR abs/2009.10924 (2020)
Coauthor Index
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