If your data distribution shifts, use self-learning

If your data distribution shifts, use self-learning

27 April 2021

Steffen Schneider

George Pachitariu

Peter V. Gehler

Oliver Bringmann

Wieland Brendel

Matthias Bethge

Papers citing "If your data distribution shifts, use self-learning"

8 / 8 papers shown

Title
Audiopedia: Audio QA with Knowledge Abhirama Subramanyam Penamakuri Kiran Chhatre Akshat Jain KELM AuLLM RALM 26 0 0 31 Dec 2024
On the Adversarial Risk of Test Time Adaptation: An Investigation into Realistic Test-Time Data Poisoning Yongyi Su Yushu Li Nanqing Liu Kui Jia Xulei Yang Chuan-Sheng Foo Xun Xu TTA AAML 41 0 0 07 Oct 2024
Test-Time Poisoning Attacks Against Test-Time Adaptation Models Tianshuo Cong Xinlei He Yun Shen Yang Zhang AAML TTA 6 5 0 16 Aug 2023
Emerging Properties in Self-Supervised Vision Transformers Mathilde Caron Hugo Touvron Ishan Misra Hervé Jégou Julien Mairal Piotr Bojanowski Armand Joulin 283 5,723 0 29 Apr 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 143 62 0 08 Dec 2020
RobustBench: a standardized adversarial robustness benchmark Francesco Croce Maksym Andriushchenko Vikash Sehwag Edoardo Debenedetti Nicolas Flammarion M. Chiang Prateek Mittal Matthias Hein VLM 205 668 0 19 Oct 2020
Confidence Regularized Self-Training Yang Zou Zhiding Yu Xiaofeng Liu B. Kumar Jinsong Wang 202 783 0 26 Aug 2019
Aggregated Residual Transformations for Deep Neural Networks Saining Xie Ross B. Girshick Piotr Dollár Z. Tu Kaiming He 261 10,106 0 16 Nov 2016