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Ruihan Wu
Ruihan Wu
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Title
Cited by
Cited by
Year
Product kernel interpolation for scalable Gaussian processes
J Gardner, G Pleiss, R Wu, K Weinberger, A Wilson
International Conference on Artificial Intelligence and Statistics, 1407-1416, 2018
502018
Correlator convolutional neural networks as an interpretable architecture for image-like quantum matter data
C Miles, A Bohrdt, R Wu, C Chiu, M Xu, G Ji, M Greiner, KQ Weinberger, ...
Nature Communications 12 (1), 1-7, 2021
222021
On Hiding Neural Networks Inside Neural Networks
C Guo, R Wu, KQ Weinberger
arXiv preprint arXiv:2002.10078, 2020
21*2020
Quadratic upper bound for recursive teaching dimension of finite VC classes
L Hu, R Wu, T Li, L Wang
Conference on Learning Theory, 1147-1156, 2017
152017
Making paper reviewing robust to bid manipulation attacks
R Wu, C Guo, F Wu, R Kidambi, L Van Der Maaten, K Weinberger
International Conference on Machine Learning, 11240-11250, 2021
82021
Scalable lattice influence maximization
W Chen, R Wu, Z Yu
IEEE Transactions on Computational Social Systems 7 (4), 956-970, 2020
82020
Online adaptation to label distribution shift
R Wu, C Guo, Y Su, KQ Weinberger
Advances in Neural Information Processing Systems 34, 11340-11351, 2021
32021
Spatial-Temporal Graph Neural Network For Interaction-Aware Vehicle Trajectory Prediction
J Chen, Y Wang, R Wu, M Campbell
2021 IEEE 17th International Conference on Automation Science and …, 2021
22021
Fixes that fail: Self-defeating improvements in machine-learning systems
R Wu, C Guo, A Hannun, L van der Maaten
Advances in Neural Information Processing Systems 34, 11745-11756, 2021
12021
Differentially Private Multi-Party Data Release for Linear Regression
R Wu, X Yang, Y Yao, J Sun, T Liu, KQ Weinberger, C Wang
The 38th Conference on Uncertainty in Artificial Intelligence, 2022
2022
Does Label Differential Privacy Prevent Label Inference Attacks?
R Wu, JP Zhou, KQ Weinberger, C Guo
arXiv preprint arXiv:2202.12968, 2022
2022
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Articles 1–11