Ke Sun - RankMe

28 papers A* 5C 1Journal 19Unranked 3

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Principled Fast and Meta Knowledge Learners for Continual Reinforcement Learning. CoRR Ke Sun, Hongming Zhang, Jun Jin, Chao Gao, Xi Chen, Wulong Liu, Linglong Kong
2025	—	`conf`	On Leveraging Unlabeled Data for Concurrent Positive-Unlabeled Classification and Robust Generation. ICIG (2) Bing Yu, Ke Sun, He Wang, Zhouchen Lin, Zhanxing Zhu
2025	J	`jnl`	Pareto adversarial robustness: balancing spatial robustness and sensitivity-based robustness. Sci. China Inf. Sci. Ke Sun, Mingjie Li, Zhouchen Lin
2024	J	`jnl`	A Distance-based Anomaly Detection Framework for Deep Reinforcement Learning. Trans. Mach. Learn. Res. Hongming Zhang, Ke Sun, Bo Xu, Linglong Kong, Martin Müller
2024	A*	`conf`	Distributional Reinforcement Learning with Regularized Wasserstein Loss. NeurIPS Ke Sun, Yingnan Zhao, Wulong Liu, Bei Jiang, Linglong Kong
2023	—	`conf`	Exploring the Training Robustness of Distributional Reinforcement Learning Against Noisy State Observations. ECML/PKDD (5) Ke Sun, Yingnan Zhao, Shangling Jui, Linglong Kong
2023	J	`jnl`	Mathematical Challenges in Deep Learning. CoRR Vahid Partovi Nia, Guojun Zhang, Ivan Kobyzev, Michael R. Metel, Xinlin Li, Ke Sun, Sobhan Hemati, Masoud Asgharian, Linglong Kong, Wulong Liu, Boxing Chen
2023	C	`conf`	Patch-level Neighborhood Interpolation: A General and Effective Graph-based Regularization Strategy. ACML Ke Sun, Bing Yu, Zhouchen Lin, Zhanxing Zhu
2022	J	`jnl`	Distributional Reinforcement Learning via Sinkhorn Iterations. CoRR Ke Sun, Yingnan Zhao, Yi Liu, Bei Jiang, Linglong Kong
2022	J	`jnl`	How Does Value Distribution in Distributional Reinforcement Learning Help Optimization? CoRR Ke Sun, Bei Jiang, Linglong Kong
2022	A*	`conf`	Identification, Amplification and Measurement: A bridge to Gaussian Differential Privacy. NeurIPS Yi Liu, Ke Sun, Bei Jiang, Linglong Kong
2022	J	`jnl`	Identification, Amplification and Measurement: A bridge to Gaussian Differential Privacy. CoRR Yi Liu, Ke Sun, Linglong Kong, Bei Jiang
2021	J	`jnl`	A Simple Unified Framework for Anomaly Detection in Deep Reinforcement Learning. CoRR Hongming Zhang, Ke Sun, Bo Xu, Linglong Kong, Martin Müller
2021	A*	`conf`	AdaGCN: Adaboosting Graph Convolutional Networks into Deep Models. ICLR Ke Sun, Zhanxing Zhu, Zhouchen Lin
2021	A*	`conf`	Damped Anderson Mixing for Deep Reinforcement Learning: Acceleration, Convergence, and Stabilization. NeurIPS Ke Sun, Yafei Wang, Yi Liu, Yingnan Zhao, Bo Pan, Shangling Jui, Bei Jiang, Linglong Kong
2021	J	`jnl`	Damped Anderson Mixing for Deep Reinforcement Learning: Acceleration, Convergence, and Stabilization. CoRR Ke Sun, Yafei Wang, Yi Liu, Yingnan Zhao, Bo Pan, Shangling Jui, Bei Jiang, Linglong Kong
2021	J	`jnl`	Exploring the Robustness of Distributional Reinforcement Learning against Noisy State Observations. CoRR Ke Sun, Yi Liu, Yingnan Zhao, Hengshuai Yao, Shangling Jui, Linglong Kong
2021	J	`jnl`	Pareto Adversarial Robustness: Balancing Spatial Robustness and Sensitivity-based Robustness. CoRR Ke Sun, Mingjie Li, Zhouchen Lin
2021	J	`jnl`	Towards Understanding Distributional Reinforcement Learning: Regularization, Optimization, Acceleration and Sinkhorn Algorithm. CoRR Ke Sun, Yingnan Zhao, Yi Liu, Enze Shi, Yafei Wang, Aref Sadeghi, Xiaodong Yan, Bei Jiang, Linglong Kong
2020	J	`jnl`	Classify and Generate Reciprocally: Simultaneous Positive-Unlabelled Learning and Conditional Generation with Extra Data. CoRR Bing Yu, Ke Sun, He Wang, Zhouchen Lin, Zhanxing Zhu
2020	A*	`conf`	Multi-Stage Self-Supervised Learning for Graph Convolutional Networks on Graphs with Few Labeled Nodes. AAAI Ke Sun, Zhouchen Lin, Zhanxing Zhu
2019	J	`jnl`	AdaGCN: Adaboosting Graph Convolutional Networks into Deep Models. CoRR Ke Sun, Zhouchen Lin, Zhanxing Zhu
2019	J	`jnl`	Enhancing the Robustness of Deep Neural Networks by Boundary Conditional GAN. CoRR Ke Sun, Zhanxing Zhu, Zhouchen Lin
2019	J	`jnl`	Multi-Stage Self-Supervised Learning for Graph Convolutional Networks. CoRR Ke Sun, Zhanxing Zhu, Zhouchen Lin
2019	J	`jnl`	Patch-level Neighborhood Interpolation: A General and Effective Graph-based Regularization Strategy. CoRR Ke Sun, Bing Yu, Zhouchen Lin, Zhanxing Zhu
2019	J	`jnl`	Towards Understanding Adversarial Examples Systematically: Exploring Data Size, Task and Model Factors. CoRR Ke Sun, Zhanxing Zhu, Zhouchen Lin
2019	—	`conf`	Virtual Adversarial Training on Graph Convolutional Networks in Node Classification. PRCV (1) Ke Sun, Zhouchen Lin, Hantao Guo, Zhanxing Zhu
2019	J	`jnl`	Virtual Adversarial Training on Graph Convolutional Networks in Node Classification. CoRR Ke Sun, Hantao Guo, Zhanxing Zhu, Zhouchen Lin