When does MAML Work the Best? An Empirical Study on Model-Agnostic Meta-Learning in NLP Applications

24 May 2020

Papers citing "When does MAML Work the Best? An Empirical Study on Model-Agnostic Meta-Learning in NLP Applications"

7 / 7 papers shown

Title
A Survey of Data-Efficient Graph Learning Wei Ju Siyu Yi Yifan Wang Qingqing Long Junyu Luo Zhiping Xiao Ming Zhang GNN 27 26 0 01 Feb 2024
An Introduction to Bi-level Optimization: Foundations and Applications in Signal Processing and Machine Learning Yihua Zhang Prashant Khanduri Ioannis C. Tsaknakis Yuguang Yao Min-Fong Hong Sijia Liu AI4CE 38 25 0 01 Aug 2023
Meta-Learning with a Geometry-Adaptive Preconditioner Suhyun Kang Duhun Hwang Moonjung Eo Taesup Kim Wonjong Rhee AI4CE 22 15 0 04 Apr 2023
Unsupervised Neural Stylistic Text Generation using Transfer learning and Adapters Vinayshekhar Bannihatti Kumar Rashmi Gangadharaiah Dan Roth 17 1 0 07 Oct 2022
Sign-MAML: Efficient Model-Agnostic Meta-Learning by SignSGD Chen Fan Parikshit Ram Sijia Liu FedML 53 16 0 15 Sep 2021
An Overview of Deep Learning Architectures in Few-Shot Learning Domain Shruti Jadon Aryan Jadon VLM 16 55 0 12 Aug 2020
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks Chelsea Finn Pieter Abbeel Sergey Levine OOD 290 11,681 0 09 Mar 2017