1 citations · 1 across the 3 of their papers we have counts for
3 papers
cs.LG2024
Boosting Meta-Training with Base Class Information for Few-Shot Learning
Weihao Jiang, Guodong Liu, Di He +1
Few-shot learning, a challenging task in machine learning, aims to learn a classifier adaptable to recognize new, unseen classes with limited labeled examples. Meta-learning has em…
cs.LG2023
Effective Medical Code Prediction via Label Internal Alignment
Guodong Liu
The clinical notes are usually typed into the system by physicians. They are typically required to be marked by standard medical codes, and each code represents a diagnosis or medi…
cs.LG2022★ 1 cited
Generating Pseudo-labels Adaptively for Few-shot Model-Agnostic Meta-Learning
Guodong Liu, Tongling Wang, Shuoxi Zhang +1
Model-Agnostic Meta-Learning (MAML) is a famous few-shot learning method that has inspired many follow-up efforts, such as ANIL and BOIL. However, as an inductive method, MAML is u…