most citedGradient-Based Meta-Learning Using Uncertainty to Weigh Loss for Few-Shot Learning

4 citations · 4 across the 3 of their papers we have counts for

collaborators

3 papers

cs.LG2023

Indeterminate Probability Theory

Tao Yang, Chuang Liu, Xiaofeng Ma +8

Complex continuous or mixed joint distributions (e.g., P(Y | z_1, z_2, ..., z_N)) generally lack closed-form solutions, often necessitating approximations such as MCMC. This paper…

cs.LG2022★ 4 cited

Gradient-Based Meta-Learning Using Uncertainty to Weigh Loss for Few-Shot Learning

Lin Ding, Peng Liu, Wenfeng Shen +2

Model-Agnostic Meta-Learning (MAML) is one of the most successful meta-learning techniques for few-shot learning. It uses gradient descent to learn commonalities between various ta…

cs.CR2022

Using EBGAN for Anomaly Intrusion Detection

Yi Cui, Wenfeng Shen, Jian Zhang +4

As an active network security protection scheme, intrusion detection system (IDS) undertakes the important responsibility of detecting network attacks in the form of malicious netw…