Chengli Tan

15 papers A* 1Journal 14
YearRankTypeTitle / Venue / Authors
2026 J jnl
Warm-start or cold-start? A comparison of generalizability in gradient-based hyperparameter tuning.
Neural Networks
Yubo Zhou, Jun Shu, Chengli Tan, Haishan Ye, Quanziang Wang, Junmin Liu, Deyu Meng, Ivor W. Tsang, Guang Dai
2025 J jnl
Frequency-Enhanced Subspace Clustering Network With Information Bottleneck.
IEEE Trans. Multim.
Mengran Hou, Mengyao Li, Chengli Tan, Junmin Liu, Jinhai Li, Huirong Li
2025 J jnl
Stabilizing Sharpness-Aware Minimization Through A Simple Renormalization Strategy.
J. Mach. Learn. Res.
Chengli Tan, Jiangshe Zhang, Junmin Liu, Yicheng Wang, Yunda Hao
2025 J jnl
Towards Understanding The Calibration Benefits of Sharpness-Aware Minimization.
CoRR
Chengli Tan, Yubo Zhou, Haishan Ye, Guang Dai, Junmin Liu, Zengjie Song, Jiangshe Zhang, Zixiang Zhao, Yunda Hao, Yong Xu
2024 J jnl
Low-dimensional intrinsic dimension reveals a phase transition in gradient-based learning of deep neural networks.
Int. J. Mach. Learn. Cybern.
Chengli Tan, Jiangshe Zhang, Junmin Liu, Zixiang Zhao
2024 J jnl
Seismic Data Interpolation via Denoising Diffusion Implicit Models With Coherence-Corrected Resampling.
IEEE Trans. Geosci. Remote. Sens.
Xiao-Li Wei, Chunxia Zhang, Hongtao Wang, Chengli Tan, Deng Xiong, Baisong Jiang, Jiangshe Zhang, Sang-Woon Kim
2024 J jnl
Sharpness-Aware Lookahead for Accelerating Convergence and Improving Generalization.
IEEE Trans. Pattern Anal. Mach. Intell.
Chengli Tan, Jiangshe Zhang, Junmin Liu, Yihong Gong
2024 J jnl
Stabilizing Sharpness-aware Minimization Through A Simple Renormalization Strategy.
CoRR
Chengli Tan, Jiangshe Zhang, Junmin Liu, Yicheng Wang, Yunda Hao
2024 J jnl
Understanding Short-Range Memory Effects in Deep Neural Networks.
IEEE Trans. Neural Networks Learn. Syst.
Chengli Tan, Jiang-She Zhang, Junmin Liu
2023 J jnl
Robust Teacher: Self-correcting pseudo-label-guided semi-supervised learning for object detection.
Comput. Vis. Image Underst.
Shijie Li, Junmin Liu, Weilin Shen, Jianyong Sun, Chengli Tan
2023 A* conf
Spherical Space Feature Decomposition for Guided Depth Map Super-Resolution.
ICCV
Zixiang Zhao, Jiangshe Zhang, Xiang Gu, Chengli Tan, Shuang Xu, Yulun Zhang, Radu Timofte, Luc Van Gool
2023 J jnl
Spherical Space Feature Decomposition for Guided Depth Map Super-Resolution.
CoRR
Zixiang Zhao, Jiangshe Zhang, Xiang Gu, Chengli Tan, Shuang Xu, Yulun Zhang, Radu Timofte, Luc Van Gool
2022 J jnl
Automatic Velocity Picking Using Unsupervised Ensemble Learning.
CoRR
Hongtao Wang, Jiangshe Zhang, Chunxia Zhang, Zixiang Zhao, Chengli Tan, Zhiyu Yang, Weifeng Geng
2022 J jnl
Trajectory-dependent Generalization Bounds for Deep Neural Networks via Fractional Brownian Motion.
CoRR
Chengli Tan, Jiangshe Zhang, Junmin Liu
2021 J jnl
Understanding Long Range Memory Effects in Deep Neural Networks.
CoRR
Chengli Tan, Jiangshe Zhang, Junmin Liu