Kuangqi Zhou

According to our database, Kuangqi Zhou authored at least 14 papers between 2020 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2023

Reachability-Aware Laplacian Representation in Reinforcement Learning.

Kaixin Wang, Kuangqi Zhou, Jiashi Feng, Bryan Hooi, Xinchao Wang

Proceedings of the International Conference on Machine Learning, 2023

Revisiting Intrinsic Reward for Exploration in Procedurally Generated Environments.

Kaixin Wang, Kuangqi Zhou, Bingyi Kang, Jiashi Feng, Shuicheng Yan

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Online Learning for Non-monotone DR-Submodular Maximization: From Full Information to Bandit Feedback.

Qixin Zhang, Zengde Deng, Zaiyi Chen, Kuangqi Zhou, Haoyuan Hu, Yu Yang

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022

Online Learning for Non-monotone Submodular Maximization: From Full Information to Bandit Feedback.

Qixin Zhang, Zengde Deng, Zaiyi Chen, Kuangqi Zhou, Haoyuan Hu, Yu Yang

CoRR, 2022

Tyger: Task-Type-Generic Active Learning for Molecular Property Prediction.

Kuangqi Zhou, Kaixin Wang, Jiashi Feng, Jian Tang, Tingyang Xu, Xinchao Wang

CoRR, 2022

Value Penalized Q-Learning for Recommender Systems.

Chengqian Gao, Ke Xu, Kuangqi Zhou, Lanqing Li, Xueqian Wang, Bo Yuan, Peilin Zhao

Proceedings of the SIGIR '22: The 45th International ACM SIGIR Conference on Research and Development in Information Retrieval, Madrid, Spain, July 11, 2022

Jointly Modelling Uncertainty and Diversity for Active Molecular Property Prediction.

Kuangqi Zhou, Kaixin Wang, Jian Tang, Jiashi Feng, Bryan Hooi, Peilin Zhao, Tingyang Xu, Xinchao Wang

Proceedings of the Learning on Graphs Conference, 2022

The Geometry of Robust Value Functions.

Kaixin Wang, Navdeep Kumar, Kuangqi Zhou, Bryan Hooi, Jiashi Feng, Shie Mannor

Proceedings of the International Conference on Machine Learning, 2022

Mimicking the Oracle: An Initial Phase Decorrelation Approach for Class Incremental Learning.

Yujun Shi, Kuangqi Zhou, Jian Liang, Zihang Jiang, Jiashi Feng, Philip H. S. Torr, Song Bai, Vincent Y. F. Tan

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

2021

Towards Better Laplacian Representation in Reinforcement Learning with Generalized Graph Drawing.

Kaixin Wang, Kuangqi Zhou, Qixin Zhang, Jie Shao, Bryan Hooi, Jiashi Feng

Proceedings of the 38th International Conference on Machine Learning, 2021

Understanding and Resolving Performance Degradation in Deep Graph Convolutional Networks.

Kuangqi Zhou, Yanfei Dong, Kaixin Wang, Wee Sun Lee, Bryan Hooi, Huan Xu, Jiashi Feng

Proceedings of the CIKM '21: The 30th ACM International Conference on Information and Knowledge Management, Virtual Event, Queensland, Australia, November 1, 2021

2020

Few-shot Classification via Adaptive Attention.

Zihang Jiang, Bingyi Kang, Kuangqi Zhou, Jiashi Feng

CoRR, 2020

Multi-Miner: Object-Adaptive Region Mining for Weakly-Supervised Semantic Segmentation.

Kuangqi Zhou, Qibin Hou, Zun Li, Jiashi Feng

CoRR, 2020

Effective Training Strategies for Deep Graph Neural Networks.

Kuangqi Zhou, Yanfei Dong, Wee Sun Lee, Bryan Hooi, Huan Xu, Jiashi Feng

CoRR, 2020