Tu, Cheng-Hao

8 publications

CVPR 2025 Lessons and Insights from a Unifying Study of Parameter-Efficient Fine-Tuning (PEFT) in Visual Recognition Zheda Mai, Ping Zhang, Cheng-Hao Tu, Hong-You Chen, Quang-Huy Nguyen, Li Zhang, Wei-Lun Chao

NeurIPS 2024 Fine-Tuning Is Fine, if Calibrated Zheda Mai, Arpita Chowdhury, Ping Zhang, Cheng-Hao Tu, Hong-You Chen, Vardaan Pahuja, Tanya Berger-Wolf, Song Gao, Charles Stewart, Yu Su, Wei-Lun Chao

NeurIPS 2023 Holistic Transfer: Towards Non-Disruptive Fine-Tuning with Partial Target Data Cheng-Hao Tu, Hong-You Chen, Zheda Mai, Jike Zhong, Vardaan Pahuja, Tanya Berger-Wolf, Song Gao, Charles Stewart, Yu Su, Wei-Lun Chao

AAAI 2023 Learning Fractals by Gradient Descent Cheng-Hao Tu, Hong-You Chen, David Carlyn, Wei-Lun Chao

ICLR 2023 On the Importance and Applicability of Pre-Training for Federated Learning Hong-You Chen, Cheng-Hao Tu, Ziwei Li, Han Wei Shen, Wei-Lun Chao

CVPR 2023 Visual Query Tuning: Towards Effective Usage of Intermediate Representations for Parameter and Memory Efficient Transfer Learning Cheng-Hao Tu, Zheda Mai, Wei-Lun Chao

CVPRW 2019 Adaptive Labeling for Deep Learning to Hash Huei-Fang Yang, Cheng-Hao Tu, Chu-Song Chen

NeurIPS 2019 Compacting, Picking and Growing for Unforgetting Continual Learning Ching-Yi Hung, Cheng-Hao Tu, Cheng-En Wu, Chien-Hung Chen, Yi-Ming Chan, Chu-Song Chen