Kezhi Kong
Kezhi Kong
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Robust optimization as data augmentation for large-scale graphs
K Kong, G Li, M Ding, Z Wu, C Zhu, B Ghanem, G Taylor, T Goldstein
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022
On the Reliability of Watermarks for Large Language Models
J Kirchenbauer, J Geiping, Y Wen, M Shu, K Saifullah, K Kong, ...
arXiv preprint arXiv:2306.04634, 2023
Data augmentation for meta-learning
R Ni, M Goldblum, A Sharaf, K Kong, T Goldstein
International Conference on Machine Learning, 8152-8161, 2021
Gradinit: Learning to initialize neural networks for stable and efficient training
C Zhu, R Ni, Z Xu, K Kong, WR Huang, T Goldstein
Advances in Neural Information Processing Systems 34, 16410-16422, 2021
VQ-GNN: A universal framework to scale up graph neural networks using vector quantization
M Ding, K Kong, J Li, C Zhu, J Dickerson, F Huang, T Goldstein
Advances in Neural Information Processing Systems 34, 6733-6746, 2021
A closer look at distribution shifts and out-of-distribution generalization on graphs
M Ding, K Kong, J Chen, J Kirchenbauer, M Goldblum, D Wipf, F Huang, ...
Shot-vae: semi-supervised deep generative models with label-aware elbo approximations
HZ Feng, K Kong, M Chen, T Zhang, M Zhu, W Chen
Proceedings of the AAAI Conference on Artificial Intelligence 35 (8), 7413-7421, 2021
GOAT: A Global Transformer on Large-scale Graphs
K Kong, J Chen, J Kirchenbauer, R Ni, CB Bruss, T Goldstein
International Conference on Machine Learning 2023, 2023
Exploring linear projections for revealing clusters, outliers, and trends in subsets of multi-dimensional datasets
J Xia, L Gao, K Kong, Y Zhao, Y Chen, X Kui, Y Liang
Journal of Visual Languages & Computing 48, 52-60, 2018
Insta-rs: Instance-wise randomized smoothing for improved robustness and accuracy
C Chen, K Kong, P Yu, J Luque, T Goldstein, F Huang
arXiv preprint arXiv:2103.04436, 2021
OpenTab: Advancing large language models as open-domain table reasoners
K Kong, J Zhang, Z Shen, B Srinivasan, C Lei, C Faloutsos, H Rangwala, ...
arXiv preprint arXiv:2402.14361, 2024
A Visual Analytics Approach for Traffic Flow Prediction Ensembles.
K Kong, Y Ma, C Ye, J Lu, X Chen, W Zhang, W Chen
PG (Short Papers and Posters), 61-64, 2018
Towards Generalized and Scalable Machine Learning on Structured Data
K Kong
Visualization of neo-epidermis formation and evaluation of wound closure using UV fluorescence excitation imaging at two wavelengths (Conference Presentation)
Y Wang, W Cai, K Kong, X Jia, RR Anderson, W Franco
Photonics in Dermatology and Plastic Surgery 2019 10851, 108510H, 2019
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