6 citations · 19 across the 5 of their papers we have counts for
4 papers · 1 filter
Boosting Multitask Learning on Graphs through Higher-Order Task Affinities
Dongyue Li, Haotian Ju, Aneesh Sharma +1
Predicting node labels on a given graph is a widely studied problem with many applications, including community detection and molecular graph prediction. This paper considers predi…
Noise Stability Optimization for Finding Flat Minima: A Hessian-based Regularization Approach
Hongyang R. Zhang, Dongyue Li, Haotian Ju
The training of over-parameterized neural networks has received much study in recent literature. An important consideration is the regularization of over-parameterized networks due…
Generalization in Graph Neural Networks: Improved PAC-Bayesian Bounds on Graph Diffusion
Haotian Ju, Dongyue Li, Aneesh Sharma +1
Graph neural networks are widely used tools for graph prediction tasks. Motivated by their empirical performance, prior works have developed generalization bounds for graph neural…
Robust Fine-Tuning of Deep Neural Networks with Hessian-based Generalization Guarantees
Haotian Ju, Dongyue Li, Hongyang R. Zhang
We consider fine-tuning a pretrained deep neural network on a target task. We study the generalization properties of fine-tuning to understand the problem of overfitting, which has…