Hopcroft, John E.

13 publications

NeurIPS 2025 Rethinking Tokenized Graph Transformers for Node Classification Jinsong Chen, Chenyang Li, Gaichao Li, John E. Hopcroft, Kun He

NeurIPS 2024 Leveraging Contrastive Learning for Enhanced Node Representations in Tokenized Graph Transformers Jinsong Chen, Hanpeng Liu, John E. Hopcroft, Kun He

ICML 2023 On the Complexity of Bayesian Generalization Yu-Zhe Shi, Manjie Xu, John E. Hopcroft, Kun He, Joshua B. Tenenbaum, Song-Chun Zhu, Ying Nian Wu, Wenjuan Han, Yixin Zhu

ICMLW 2023 PIAT: Parameter Interpolation Based Adversarial Training for Image Classification Kun He, Xin Liu, Yichen Yang, Zhou Qin, Weigao Wen, Hui Xue', John E. Hopcroft

CVPR 2022 Stochastic Variance Reduced Ensemble Adversarial Attack for Boosting the Adversarial Transferability Yifeng Xiong, Jiadong Lin, Min Zhang, John E. Hopcroft, Kun He

ICLR 2020 Nesterov Accelerated Gradient and Scale Invariance for Adversarial Attacks Jiadong Lin, Chuanbiao Song, Kun He, Liwei Wang, John E. Hopcroft

ICLR 2020 Robust Local Features for Improving the Generalization of Adversarial Training Chuanbiao Song, Kun He, Jiadong Lin, Liwei Wang, John E. Hopcroft

ICLR 2019 Improving the Generalization of Adversarial Training with Domain Adaptation Chuanbiao Song, Kun He, Liwei Wang, John E. Hopcroft

ECML-PKDD 2017 Local Lanczos Spectral Approximation for Community Detection Pan Shi, Kun He, David Bindel, John E. Hopcroft

ICLR 2017 Snapshot Ensembles: Train 1, Get M for Free Gao Huang, Yixuan Li, Geoff Pleiss, Zhuang Liu, John E. Hopcroft, Kilian Q. Weinberger

ICLR 2016 Convergent Learning: Do Different Neural Networks Learn the Same Representations? Yixuan Li, Jason Yosinski, Jeff Clune, Hod Lipson, John E. Hopcroft

ECML-PKDD 2012 Feature-Enhanced Probabilistic Models for Diffusion Network Inference Liaoruo Wang, Stefano Ermon, John E. Hopcroft

ICML 2005 Error Bounds for Correlation Clustering Thorsten Joachims, John E. Hopcroft