Yefan Zhou

According to our database, Yefan Zhou authored at least 13 papers between 2019 and 2024.

Collaborative distances:

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

2024

AlphaPruning: Using Heavy-Tailed Self Regularization Theory for Improved Layer-wise Pruning of Large Language Models.

Haiquan Lu, Yefan Zhou, Shiwei Liu, Zhangyang Wang, Michael W. Mahoney, Yaoqing Yang

CoRR, 2024

Sharpness-diversity tradeoff: improving flat ensembles with SharpBalance.

Haiquan Lu, Xiaotian Liu, Yefan Zhou, Qunli Li, Kurt Keutzer, Michael W. Mahoney, Yujun Yan, Huanrui Yang, Yaoqing Yang

CoRR, 2024

MD tree: a model-diagnostic tree grown on loss landscape.

Yefan Zhou, Jianlong Chen, Qinxue Cao, Konstantin Schürholt, Yaoqing Yang

Proceedings of the Forty-first International Conference on Machine Learning, 2024

AlphaLoRA: Assigning LoRA Experts Based on Layer Training Quality.

Peijun Qing, Chongyang Gao, Yefan Zhou, Xingjian Diao, Yaoqing Yang, Soroush Vosoughi

Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024

Model Balancing Helps Low-data Training and Fine-tuning.

Zihang Liu, Yuanzhe Hu, Tianyu Pang, Yefan Zhou, Pu Ren, Yaoqing Yang

Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024

2023

Temperature Balancing, Layer-wise Weight Analysis, and Neural Network Training.

Yefan Zhou, Tianyu Pang, Keqin Liu, Charles H. Martin, Michael W. Mahoney, Yaoqing Yang

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

A Three-regime Model of Network Pruning.

Yefan Zhou, Yaoqing Yang, Arin Chang, Michael W. Mahoney

Proceedings of the International Conference on Machine Learning, 2023

2022

Learn to Grasp with Less Supervision: A Data-Efficient Maximum Likelihood Grasp Sampling Loss.

Xinghao Zhu, Yefan Zhou, Yongxiang Fan, Lingfeng Sun, Jianyu Chen, Masayoshi Tomizuka

Proceedings of the 2022 International Conference on Robotics and Automation, 2022

2021

Learn to Grasp with Less Supervision: A Data-Efficient Maximum Likelihood Grasp Sampling Loss.

Xinghao Zhu, Yefan Zhou, Yongxiang Fan, Masayoshi Tomizuka

CoRR, 2021

A Dataset-Dispersion Perspective on Reconstruction Versus Recognition in Single-View 3D Reconstruction Networks.

Yefan Zhou, Yiru Shen, Yujun Yan, Chen Feng, Yaoqing Yang

Proceedings of the International Conference on 3D Vision, 2021

2020

Measurements of the Conditional Dependence Structure Among Carbon, Fossil Energy and Renewable Energy Prices: Vine Copula Based GJR-GARCH Model.

Yefan Zhou, Jianxu Liu, Jirakom Sirisrisakulchai, Songsak Sriboonchitta

Proceedings of the Integrated Uncertainty in Knowledge Modelling and Decision Making, 2020

A Two-Stream Network For Driving Hand Gesture Recognition.

Yefan Zhou, Zhao Lv, Chaoqun Wang, Shengli Zhang

Proceedings of the 20th International Conference on Data Mining Workshops, 2020

2019

Factors Affecting Carbon Emissons in the G7 and BRICS Countries: Evidence from Quantile Regression.

Yefan Zhou, Jirakom Sirisrisakulchai, Jianxu Liu, Songsak Sriboonchitta

Proceedings of the Integrated Uncertainty in Knowledge Modelling and Decision Making, 2019