94 citations · 263 across the 14 of their papers we have counts for
20 papers
You are caught stealing my winning lottery ticket! Making a lottery ticket claim its ownership
Xuxi Chen, Tianlong Chen, Zhenyu Zhang +1
Despite tremendous success in many application scenarios, the training and inference costs of using deep learning are also rapidly increasing over time. The lottery ticket hypothes…
CAP: Co-Adversarial Perturbation on Weights and Features for Improving Generalization of Graph Neural Networks
Haotian Xue, Kaixiong Zhou, Tianlong Chen +4
Despite the recent advances of graph neural networks (GNNs) in modeling graph data, the training of GNNs on large datasets is notoriously hard due to the overfitting. Adversarial t…
Sanity Checks for Lottery Tickets: Does Your Winning Ticket Really Win the Jackpot?
Xiaolong Ma, Geng Yuan, Xuan Shen +8
There have been long-standing controversies and inconsistencies over the experiment setup and criteria for identifying the "winning ticket" in literature. To reconcile such, we rev…
Graph Contrastive Learning Automated
Yuning You, Tianlong Chen, Yang Shen +1
Self-supervised learning on graph-structured data has drawn recent interest for learning generalizable, transferable and robust representations from unlabeled graphs. Among many, g…
Sparse and Imperceptible Adversarial Attack via a Homotopy Algorithm
Mingkang Zhu, Tianlong Chen, Zhangyang Wang
Sparse adversarial attacks can fool deep neural networks (DNNs) by only perturbing a few pixels (regularized by l_0 norm). Recent efforts combine it with another l_infty impercepti…
Efficient Lottery Ticket Finding: Less Data is More
Zhenyu Zhang, Xuxi Chen, Tianlong Chen +1
The lottery ticket hypothesis (LTH) reveals the existence of winning tickets (sparse but critical subnetworks) for dense networks, that can be trained in isolation from random init…