Xin Gao

On the Decision Boundary of Deep Neural Networks

2018 · arXiv (Cornell University)

While deep learning models and techniques have achieved great empirical success, our understanding of the source of success in many aspects remains very limited. In an attempt to bridge the gap, we investigate the decision …

A Framework For Differentiable Discovery Of Graph Algorithms

2021

Recently there is a surge of interests in using graph neural networks (GNNs) to learn algorithms. However, these works focus more on imitating existing algorithms, and are limited in two important aspects: the search space …

Unsupervised Mitigating Gender Bias by Character Components: A Case Study of Chinese Word Embedding

2022

Word embeddings learned from massive text collections have demonstrated significant levels of discriminative biases. However, debiasing on the Chinese language, one of the most spoken languages, has been less explored. Meanwhile, existing literature relies on …

RNN enhanced Compartmental Model for Infectious Disease Prediction

2024

COVID-19 has caused a pandemic on a global scale and brought about harm to politics, economy, and other fields. It is of great significance to build an epidemic analysis model for better understanding pandemic transmission …