Jinzhen Wang

According to our database, Jinzhen Wang authored at least 22 papers between 2014 and 2025.

Collaborative distances:

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

2025

Rethinking the Potential of Layer Freezing for Efficient DNN Training.

Chence Yang, Ci Zhang, Le Lu, Qitao Tan, Sheng Li, Ao Li, Xulong Tang, Shaoyi Huang, Jinzhen Wang, Guoming Li, Jundong Li, Xiaoming Zhai, Jin Lu, Geng Yuan

CoRR, August, 2025

NeurLZ: An Online Neural Learning-based Method to Enhance Scientific Lossy Compression.

Wenqi Jia, Zhewen Hu, Youyuan Liu, Boyuan Zhang, Jinzhen Wang, Jinyang Liu, Wei Niu, Stavros Kalafatis, Junzhou Huang, Sian Jin, Daoce Wang, Jiannan Tian, Miao Yin

Proceedings of the 39th ACM International Conference on Supercomputing, 2025

2024

NeurLZ: On Enhancing Lossy Compression Performance based on Error-Controlled Neural Learning for Scientific Data.

Wenqi Jia, Youyuan Liu, Zhewen Hu, Jinzhen Wang, Boyuan Zhang, Wei Niu, Junzhou Huang, Stavros Kalafatis, Sian Jin, Miao Yin

CoRR, 2024

Tango: A Cross-layer Approach to Managing I/O Interference over Local Ephemeral Storage.

Zhenbo Qiao, Qirui Tian, Zhenlu Qin, Jinzhen Wang, Qing Liu, Norbert Podhorszki, Scott Klasky, Hongjian Zhu

Proceedings of the International Conference for High Performance Computing, 2024

GWLZ: A Group-wise Learning-based Lossy Compression Framework for Scientific Data.

Wenqi Jia, Sian Jin, Jinzhen Wang, Wei Niu, Dingwen Tao, Miao Yin

Proceedings of the 14th Workshop on AI and Scientific Computing at Scale using Flexible Computing Infrastructures, 2024

A Generic Performance Metric for Scientific Data Compression.

Zhenlu Qin, Jessie Gu, Maggie Liu, Jinzhen Wang, Hongjian Zhu

Proceedings of the 20th IEEE International Conference on e-Science, 2024

QualityNet: Error-bounded Lossy Compression Quality Prediction via Deep Surrogate.

Khondoker Mirazul Mumenin, Dong Dai, Jinzhen Wang, Sheng Di

Proceedings of the IEEE International Conference on Big Data, 2024

2023

zPerf: A Statistical Gray-Box Approach to Performance Modeling and Extrapolation for Scientific Lossy Compression.

Jinzhen Wang, Qi Chen, Tong Liu, Qing Liu, Xubin He

IEEE Trans. Computers, September, 2023

High-Ratio Lossy Compression: Exploring the Autoencoder to Compress Scientific Data.

Tong Liu, Jinzhen Wang, Qing Liu, Shakeel Alibhai, Tao Lu, Xubin He

IEEE Trans. Big Data, February, 2023

Improving Progressive Retrieval for HPC Scientific Data using Deep Neural Network.

Jinzhen Wang, Xin Liang, Ben Whitney, Jieyang Chen, Qian Gong, Xubin He, Lipeng Wan, Scott Klasky, Norbert Podhorszki, Qing Liu

Proceedings of the 39th IEEE International Conference on Data Engineering, 2023

2022

Locality-based transfer learning on compression autoencoder for efficient scientific data lossy compression.

Nan Wang, Tong Liu, Jinzhen Wang, Qing Liu, Shakeel Alibhai, Xubin He

J. Netw. Comput. Appl., 2022

Analyzing the Impact of Lossy Data Reduction on Volume Rendering of Cosmology Data.

Jinzhen Wang, Pascal Grosset, Terece L. Turton, James P. Ahrens

Proceedings of the 8th IEEE/ACM International Workshop on Data Analysis and Reduction for Big Scientific Data, 2022

2021

Unbalanced Parallel I/O: An Often-Neglected Side Effect of Lossy Scientific Data Compression.

Xinying Wang, Lipeng Wan, Jieyang Chen, Qian Gong, Ben Whitney, Jinzhen Wang, Ana Gainaru, Qing Liu, Norbert Podhorszki, Dongfang Zhao, Feng Yan, Scott Klasky

Proceedings of the 2021 7th International Workshop on Data Analysis and Reduction for Big Scientific Data, 2021

Reducing the Training Overhead of the HPC Compression Autoencoder via Dataset Proportioning.

Tong Liu, Shakeel Alibhai, Jinzhen Wang, Qing Liu, Xubin He

Proceedings of the IEEE International Conference on Networking, Architecture and Storage, 2021

2020

Compression Ratio Modeling and Estimation across Error Bounds for Lossy Compression.

Jinzhen Wang, Tong Liu, Qing Liu, Xubin He, Huizhang Luo, Weiming He

IEEE Trans. Parallel Distributed Syst., 2020

2019

Exploring Transfer Learning to Reduce Training Overhead of HPC Data in Machine Learning.

Tong Liu, Shakeel Alibhai, Jinzhen Wang, Qing Liu, Xubin He, Chentao Wu

Proceedings of the 2019 IEEE International Conference on Networking, 2019

Identifying Latent Reduced Models to Precondition Lossy Compression.

Huizhang Luo, Dan Huang, Qing Liu, Zhenbo Qiao, Hong Jiang, Jing Bi, Haitao Yuan, Mengchu Zhou, Jinzhen Wang, Zhenlu Qin

Proceedings of the 2019 IEEE International Parallel and Distributed Processing Symposium, 2019

2018

SIRIUS: Enabling Progressive Data Exploration for Extreme-Scale Scientific Data.

Zhenbo Qiao, Tao Lu, Huizhang Luo, Qing Liu, Scott Klasky, Norbert Podhorszki, Jinzhen Wang

IEEE Trans. Multi Scale Comput. Syst., 2018

2016

Research of Recognition System of Web Intrusion Detection Based on Storm.

Bo Li, Jinzhen Wang, Ping Zhao, Zhongjiang Yan, Mao Yang

Proceedings of the Fifth International Conference on Network, Communication and Computing, 2016

2015

Parameter estimation of chirp signal under low SNR.

Jinzhen Wang, Shaoying Su, Zengping Chen

Sci. China Inf. Sci., 2015

2014

Accurate parameters estimation of chirp signal in low SNR.

Jinzhen Wang, Shaoying Su, Zengping Chen

Proceedings of the International Conference on Audio, 2014

Detection of LFM signals in low SNR based on STFT and wavelet denoising.

Yu Duan, Jinzhen Wang, Shaoying Su, Zengping Chen

Proceedings of the International Conference on Audio, 2014