most citedCan Directed Graph Neural Networks be Adversarially Robust?

1 citations · 3 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV20241 cited

Optimal Eye Surgeon: Finding Image Priors through Sparse Generators at Initialization

Avrajit Ghosh, Xitong Zhang, Kenneth K. Sun +3

We introduce Optimal Eye Surgeon (OES), a framework for pruning and training deep image generator networks. Typically, untrained deep convolutional networks, which include image sa…

cs.CL2024

Towards Understanding Task-agnostic Debiasing Through the Lenses of Intrinsic Bias and Forgetfulness

Guangliang Liu, Milad Afshari, Xitong Zhang +5

While task-agnostic debiasing provides notable generalizability and reduced reliance on downstream data, its impact on language modeling ability and the risk of relearning social b…

cs.LG2023

PAC-tuning:Fine-tuning Pretrained Language Models with PAC-driven Perturbed Gradient Descent

Guangliang Liu, Zhiyu Xue, Xitong Zhang +2

Fine-tuning pretrained language models (PLMs) for downstream tasks is a large-scale optimization problem, in which the choice of the training algorithm critically determines how we…

cs.LG20231 cited

Can Directed Graph Neural Networks be Adversarially Robust?

Zhichao Hou, Xitong Zhang, Wei Wang +2

The existing research on robust Graph Neural Networks (GNNs) fails to acknowledge the significance of directed graphs in providing rich information about networks' inherent structu…

cs.LG20231 cited

Implicit regularization in Heavy-ball momentum accelerated stochastic gradient descent

Avrajit Ghosh, He Lyu, Xitong Zhang +1

It is well known that the finite step-size () in Gradient Descent (GD) implicitly regularizes solutions to flatter minima. A natural question to ask is "Does the momentum parame…