Yet Meta Learning Can Adapt Fast, It Can Also Break Easily

2 September 2020

Papers citing "Yet Meta Learning Can Adapt Fast, It Can Also Break Easily"

4 / 4 papers shown

Title
Rethinking the Number of Shots in Robust Model-Agnostic Meta-Learning Xiaoyue Duan Guoliang Kang Runqi Wang Shumin Han Shenjun Xue Tian Wang Baochang Zhang 29 2 0 28 Nov 2022
On Fast Adversarial Robustness Adaptation in Model-Agnostic Meta-Learning Ren Wang Kaidi Xu Sijia Liu Pin-Yu Chen Tsui-Wei Weng Chuang Gan Meng Wang AAML 21 46 0 20 Feb 2021
Delta-encoder: an effective sample synthesis method for few-shot object recognition Eli Schwartz Leonid Karlinsky J. Shtok Sivan Harary Mattias Marder Rogerio Feris Abhishek Kumar Raja Giryes A. Bronstein 192 351 0 12 Jun 2018
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks Chelsea Finn Pieter Abbeel Sergey Levine OOD 362 11,684 0 09 Mar 2017