Holistic Transfer: Towards Non-Disruptive Fine-Tuning with Partial
Target Data

Holistic Transfer: Towards Non-Disruptive Fine-Tuning with Partial Target Data

2 November 2023

Tanya Berger-Wolf

Charles V. Stewart

Wei-Lun Chao

Papers citing "Holistic Transfer: Towards Non-Disruptive Fine-Tuning with Partial Target Data"

7 / 7 papers shown

Title
Class-Incremental Exemplar Compression for Class-Incremental Learning Zilin Luo Yaoyao Liu Bernt Schiele Qianru Sun VLM CLL 73 44 0 24 Mar 2023
Trainable Projected Gradient Method for Robust Fine-tuning Junjiao Tian Xiaoliang Dai Chih-Yao Ma Zecheng He Yen-Cheng Liu Z. Kira 43 30 0 19 Mar 2023
Towards Understanding and Mitigating Dimensional Collapse in Heterogeneous Federated Learning Yujun Shi Jian Liang Wenqing Zhang Vincent Y. F. Tan Song Bai FedML 69 54 0 01 Oct 2022
Gradual Domain Adaptation without Indexed Intermediate Domains Hong-You Chen Wei-Lun Chao CLL 49 39 0 11 Jul 2022
SWAD: Domain Generalization by Seeking Flat Minima Junbum Cha Sanghyuk Chun Kyungjae Lee Han-Cheol Cho Seunghyun Park Yunsung Lee Sungrae Park MoMe 216 422 0 17 Feb 2021
Scaling Up Visual and Vision-Language Representation Learning With Noisy Text Supervision Chao Jia Yinfei Yang Ye Xia Yi-Ting Chen Zarana Parekh Hieu H. Pham Quoc V. Le Yun-hsuan Sung Zhen Li Tom Duerig VLM CLIP 293 3,683 0 11 Feb 2021
In-N-Out: Pre-Training and Self-Training using Auxiliary Information for Out-of-Distribution Robustness Sang Michael Xie Ananya Kumar Robbie Jones Fereshte Khani Tengyu Ma Percy Liang OOD 153 62 0 08 Dec 2020