Kuangqi Zhou - RankMe

18 papers A* 6A 2Journal 9Unranked 1

Year	Rank	Type	Title / Venue / Authors
2023	A	`conf`	Online Learning for Non-monotone DR-Submodular Maximization: From Full Information to Bandit Feedback. AISTATS Qixin Zhang, Zengde Deng, Zaiyi Chen, Kuangqi Zhou, Haoyuan Hu, Yu Yang
2023	A*	`conf`	Reachability-Aware Laplacian Representation in Reinforcement Learning. ICML Kaixin Wang, Kuangqi Zhou, Jiashi Feng, Bryan Hooi, Xinchao Wang
2023	A*	`conf`	Revisiting Intrinsic Reward for Exploration in Procedurally Generated Environments. ICLR Kaixin Wang, Kuangqi Zhou, Bingyi Kang, Jiashi Feng, Shuicheng Yan
2022	—	`conf`	Jointly Modelling Uncertainty and Diversity for Active Molecular Property Prediction. LoG Kuangqi Zhou, Kaixin Wang, Jian Tang, Jiashi Feng, Bryan Hooi, Peilin Zhao, Tingyang Xu, Xinchao Wang
2022	A*	`conf`	Mimicking the Oracle: An Initial Phase Decorrelation Approach for Class Incremental Learning. CVPR Yujun Shi, Kuangqi Zhou, Jian Liang, Zihang Jiang, Jiashi Feng, Philip H. S. Torr, Song Bai, Vincent Y. F. Tan
2022	J	`jnl`	Online Learning for Non-monotone Submodular Maximization: From Full Information to Bandit Feedback. CoRR Qixin Zhang, Zengde Deng, Zaiyi Chen, Kuangqi Zhou, Haoyuan Hu, Yu Yang
2022	J	`jnl`	Reachability-Aware Laplacian Representation in Reinforcement Learning. CoRR Kaixin Wang, Kuangqi Zhou, Jiashi Feng, Bryan Hooi, Xinchao Wang
2022	A*	`conf`	The Geometry of Robust Value Functions. ICML Kaixin Wang, Navdeep Kumar, Kuangqi Zhou, Bryan Hooi, Jiashi Feng, Shie Mannor
2022	J	`jnl`	The Geometry of Robust Value Functions. CoRR Kaixin Wang, Navdeep Kumar, Kuangqi Zhou, Bryan Hooi, Jiashi Feng, Shie Mannor
2022	J	`jnl`	Tyger: Task-Type-Generic Active Learning for Molecular Property Prediction. CoRR Kuangqi Zhou, Kaixin Wang, Jiashi Feng, Jian Tang, Tingyang Xu, Xinchao Wang
2022	A*	`conf`	Value Penalized Q-Learning for Recommender Systems. SIGIR Chengqian Gao, Ke Xu, Kuangqi Zhou, Lanqing Li, Xueqian Wang, Bo Yuan, Peilin Zhao
2021	J	`jnl`	Mimicking the Oracle: An Initial Phase Decorrelation Approach for Class Incremental Learning. CoRR Yujun Shi, Kuangqi Zhou, Jian Liang, Zihang Jiang, Jiashi Feng, Philip H. S. Torr, Song Bai, Vincent Y. F. Tan
2021	A*	`conf`	Towards Better Laplacian Representation in Reinforcement Learning with Generalized Graph Drawing. ICML Kaixin Wang, Kuangqi Zhou, Qixin Zhang, Jie Shao, Bryan Hooi, Jiashi Feng
2021	J	`jnl`	Towards Better Laplacian Representation in Reinforcement Learning with Generalized Graph Drawing. CoRR Kaixin Wang, Kuangqi Zhou, Qixin Zhang, Jie Shao, Bryan Hooi, Jiashi Feng
2021	A	`conf`	Understanding and Resolving Performance Degradation in Deep Graph Convolutional Networks. CIKM Kuangqi Zhou, Yanfei Dong, Kaixin Wang, Wee Sun Lee, Bryan Hooi, Huan Xu, Jiashi Feng
2020	J	`jnl`	Effective Training Strategies for Deep Graph Neural Networks. CoRR Kuangqi Zhou, Yanfei Dong, Wee Sun Lee, Bryan Hooi, Huan Xu, Jiashi Feng
2020	J	`jnl`	Few-shot Classification via Adaptive Attention. CoRR Zihang Jiang, Bingyi Kang, Kuangqi Zhou, Jiashi Feng
2020	J	`jnl`	Multi-Miner: Object-Adaptive Region Mining for Weakly-Supervised Semantic Segmentation. CoRR Kuangqi Zhou, Qibin Hou, Zun Li, Jiashi Feng