4 papers
Long-Tailed Recognition via Information-Preservable Two-Stage Learning
Fudong Lin, Xu Yuan
The imbalance (or long-tail) is the nature of many real-world data distributions, which often induces the undesirable bias of deep classification models toward frequent classes, re…
Towards Interpretable Adversarial Examples via Sparse Adversarial Attack
Fudong Lin, Jiadong Lou, Hao Wang +2
Sparse attacks are to optimize the magnitude of adversarial perturbations for fooling deep neural networks (DNNs) involving only a few perturbed pixels (i.e., under the l0 constrai…
Do Protein Transformers Have Biological Intelligence?
Fudong Lin, Wanrou Du, Jinchan Liu +5
Deep neural networks, particularly Transformers, have been widely adopted for predicting the functional properties of proteins. In this work, we focus on exploring whether Protein…
ECGN: A Cluster-Aware Approach to Graph Neural Networks for Imbalanced Classification
Bishal Thapaliya, Anh Nguyen, Yao Lu +7
Classifying nodes in a graph is a common problem. The ideal classifier must adapt to any imbalances in the class distribution. It must also use information in the clustering struct…