32 citations · 122 across the 21 of their papers we have counts for
4 papers · 1 filter
Meta Learning Low Rank Covariance Factors for Energy-Based Deterministic Uncertainty
Jeffrey Willette, Hae Beom Lee, Juho Lee +1
Numerous recent works utilize bi-Lipschitz regularization of neural network layers to preserve relative distances between data instances in the feature spaces of each layer. This d…
Sequential Reptile: Inter-Task Gradient Alignment for Multilingual Learning
Seanie Lee, Hae Beom Lee, Juho Lee +1
Multilingual models jointly pretrained on multiple languages have achieved remarkable performance on various multilingual downstream tasks. Moreover, models finetuned on a single m…
Online Hyperparameter Meta-Learning with Hypergradient Distillation
Hae Beom Lee, Hayeon Lee, Jaewoong Shin +3
Many gradient-based meta-learning methods assume a set of parameters that do not participate in inner-optimization, which can be considered as hyperparameters. Although such hyperp…
Large-Scale Meta-Learning with Continual Trajectory Shifting
Jaewoong Shin, Hae Beom Lee, Boqing Gong +1
Meta-learning of shared initialization parameters has shown to be highly effective in solving few-shot learning tasks. However, extending the framework to many-shot scenarios, whic…