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ORCIDYefan Zhou
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2020 – today
- 2024
[c12]Zihang Liu, Yuanzhe Hu, Tianyu Pang, Yefan Zhou, Pu Ren, Yaoqing Yang:
Model Balancing Helps Low-data Training and Fine-tuning. EMNLP 2024: 1311-1331- [c11]Peijun Qing, Chongyang Gao, Yefan Zhou, Xingjian Diao, Yaoqing Yang, Soroush Vosoughi:
AlphaLoRA: Assigning LoRA Experts Based on Layer Training Quality. EMNLP 2024: 20511-20523 - [c10]Yefan Zhou, Jianlong Chen, Qinxue Cao, Konstantin Schürholt, Yaoqing Yang:
MD tree: a model-diagnostic tree grown on loss landscape. ICML 2024 - [c9]Haiquan Lu, Xiaotian Liu, Yefan Zhou, Qunli Li, Kurt Keutzer, Michael W. Mahoney, Yujun Yan, Huanrui Yang, Yaoqing Yang:
Sharpness-diversity tradeoff: improving flat ensembles with SharpBalance. NeurIPS 2024 - [c8]Haiquan Lu, Yefan Zhou, Shiwei Liu, Zhangyang Wang, Michael W. Mahoney, Yaoqing Yang:
AlphaPruning: Using Heavy-Tailed Self Regularization Theory for Improved Layer-wise Pruning of Large Language Models. NeurIPS 2024 - [i9]Yefan Zhou, Jianlong Chen, Qinxue Cao, Konstantin Schürholt, Yaoqing Yang:
MD tree: a model-diagnostic tree grown on loss landscape. CoRR abs/2406.16988 (2024) - [i8]Haiquan Lu, Xiaotian Liu, Yefan Zhou, Qunli Li, Kurt Keutzer, Michael W. Mahoney, Yujun Yan, Huanrui Yang, Yaoqing Yang:
Sharpness-diversity tradeoff: improving flat ensembles with SharpBalance. CoRR abs/2407.12996 (2024) - [i7]Peijun Qing, Chongyang Gao, Yefan Zhou, Xingjian Diao, Yaoqing Yang, Soroush Vosoughi:
AlphaLoRA: Assigning LoRA Experts Based on Layer Training Quality. CoRR abs/2410.10054 (2024) - [i6]Haiquan Lu, Yefan Zhou, Shiwei Liu, Zhangyang Wang, Michael W. Mahoney, Yaoqing Yang:
AlphaPruning: Using Heavy-Tailed Self Regularization Theory for Improved Layer-wise Pruning of Large Language Models. CoRR abs/2410.10912 (2024) - [i5]Zihang Liu, Yuanzhe Hu, Tianyu Pang, Yefan Zhou, Pu Ren, Yaoqing Yang:
Model Balancing Helps Low-data Training and Fine-tuning. CoRR abs/2410.12178 (2024) - 2023
- [c7]Yefan Zhou, Yaoqing Yang, Arin Chang, Michael W. Mahoney:
A Three-regime Model of Network Pruning. ICML 2023: 42790-42809 - [c6]Yefan Zhou, Tianyu Pang, Keqin Liu, Charles H. Martin, Michael W. Mahoney, Yaoqing Yang:
Temperature Balancing, Layer-wise Weight Analysis, and Neural Network Training. NeurIPS 2023 - [i4]Yefan Zhou, Yaoqing Yang, Arin Chang, Michael W. Mahoney:
A Three-regime Model of Network Pruning. CoRR abs/2305.18383 (2023) - [i3]Yefan Zhou, Tianyu Pang, Keqin Liu, Charles H. Martin, Michael W. Mahoney, Yaoqing Yang:
Temperature Balancing, Layer-wise Weight Analysis, and Neural Network Training. CoRR abs/2312.00359 (2023) - 2022
- [c5]Xinghao Zhu, Yefan Zhou, Yongxiang Fan, Lingfeng Sun, Jianyu Chen, Masayoshi Tomizuka:
Learn to Grasp with Less Supervision: A Data-Efficient Maximum Likelihood Grasp Sampling Loss. ICRA 2022: 721-727 - 2021
- [c4]Yefan Zhou, Yiru Shen, Yujun Yan
, Chen Feng, Yaoqing Yang:
A Dataset-Dispersion Perspective on Reconstruction Versus Recognition in Single-View 3D Reconstruction Networks. 3DV 2021: 1331-1340 - [i2]Xinghao Zhu, Yefan Zhou, Yongxiang Fan, Masayoshi Tomizuka:
Learn to Grasp with Less Supervision: A Data-Efficient Maximum Likelihood Grasp Sampling Loss. CoRR abs/2110.01379 (2021) - [i1]Yefan Zhou, Yiru Shen, Yujun Yan, Chen Feng, Yaoqing Yang:
A Dataset-Dispersion Perspective on Reconstruction Versus Recognition in Single-View 3D Reconstruction Networks. CoRR abs/2111.15158 (2021) - 2020
- [c3]Yefan Zhou, Zhao Lv, Chaoqun Wang, Shengli Zhang:
A Two-Stream Network For Driving Hand Gesture Recognition. ICDM (Workshops) 2020: 553-560 - [c2]Yefan Zhou, Jianxu Liu, Jirakom Sirisrisakulchai, Songsak Sriboonchitta:
Measurements of the Conditional Dependence Structure Among Carbon, Fossil Energy and Renewable Energy Prices: Vine Copula Based GJR-GARCH Model. IUKM 2020: 322-334
2010 – 2019
- 2019
- [c1]Yefan Zhou, Jirakom Sirisrisakulchai, Jianxu Liu, Songsak Sriboonchitta:
Factors Affecting Carbon Emissons in the G7 and BRICS Countries: Evidence from Quantile Regression. IUKM 2019: 406-417
Coauthor Index
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