Ke Sun (孙科)
Cited by
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Multi-Stage Self-Supervised Learning for Graph Convolutional Networks on Graphs with Few Labeled Nodes
K Sun, Z Zhu, Z Lin
AAAI 2020, 2019
AdaGCN: Adaboosting Graph Convolutional Networks into Deep Models
K Sun, Z Lin, Z Zhu
ICLR 2021, 2019
Virtual Adversarial Training on Graph Convolutional Networks in Node Classification
K Sun, H Guo, Z Zhu, Z Lin
PRCV2019, 2019
Towards Understanding Adversarial Examples Systematically: Exploring Data Size, Task and Model Factors
K Sun, Z Zhu, Z Lin
arXiv preprint arXiv:1902.11019,, 2019
Enhancing the Robustness of Deep Neural Networks by Boundary Conditional GAN
K Sun, Z Zhu, Z Lin
arXiv preprint arXiv:1902.11029,, 2019
Exploring the Training Robustness of Distributional Reinforcement Learning against Noisy State Observations
K Sun, Y Zhao, S Jui, L Kong
ECML-PKDD 2023, 2021
Damped Anderson Mixing for Deep Reinforcement Learning: Acceleration, Convergence, and Stabilization
K Sun, Y Wang, Y Liu, Y Zhao, B Pan, S Jui, B Jiang, L Kong
NeurIPS 2021, 2021
Identification, Amplification and Measurement: A bridge to Gaussian Differential Privacy
Y Liu, K Sun, L Kong, B Jiang
NeurIPS 2022, 2022
How Does Value Distribution in Distributional Reinforcement Learning Help Optimization?
K Sun, B Jiang, L Kong
arXiv preprint arXiv:2209.14513, 2022
Distributional reinforcement learning via sinkhorn iterations
K Sun, Y Zhao, Y Liu, W Liu, B Jiang, L Kong
arXiv preprint arXiv:2202.00769, 2022
An adaptive model checking test for functional linear model
E Shi, Y Liu, K Sun, L Li, L Kong
arXiv preprint arXiv:2204.01831, 2022
Pareto Adversarial Robustness: Balancing Spatial Robustness and Sensitivity-based Robustness
K Sun, M Li, Z Lin
SCIENCE CHINA Information Sciences, 2021
Interpreting Distributional Reinforcement Learning: A Regularization Perspective
K Sun, Y Zhao, Y Liu, E Shi, Y Wang, X Yan, B Jiang, L Kong
arXiv preprint arXiv:2110.03155, 2021
Patch-level neighborhood interpolation: A general and effective graph-based regularization strategy
K Sun, B Yu, Z Lin, Z Zhu
Asian Conference on Machine Learning (ACML) 2023, 2019
A Simple Unified Framework for Anomaly Detection in Deep Reinforcement Learning
H Zhang, K Sun, B Xu, L Kong, M Müller
arXiv preprint arXiv:2109.09889, 2021
Classify and Generate Reciprocally: Simultaneous Positive-Unlabelled Learning and Conditional Generation with Extra Data
B Yu, K Sun, H Wang, Z Lin, Z Zhu
arXiv preprint arXiv:2006.07841, 2020
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