Zheqing Zhu

According to our database, Zheqing Zhu authored at least 17 papers between 2017 and 2025.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2025

ExpDrug: An explainable drug recommendation model based on space feature mapping.

Xuan Lu, Yanhong Hao, Furong Peng, Zheqing Zhu, Zhanwen Cheng

Neurocomputing, 2025

2024

Learning to bid and rank together in recommendation systems.

Geng Ji, Wentao Jiang, Jiang Li, Fahmid Morshed Fahid, Zhengxing Chen, Yinghua Li, Jun Xiao, Chongxi Bao, Zheqing Zhu

Mach. Learn., May, 2024

Correction to: Learning to bid and rank together in recommendation systems.

Geng Ji, Wentao Jiang, Jiang Li, Fahmid Morshed Fahid, Zhengxing Chen, Yinghua Li, Jun Xiao, Chongxi Bao, Zheqing Zhu

Mach. Learn., 2024

Epinet for Content Cold Start.

Hong Jun Jeon, Songbin Liu, Yuantong Li, Jie Lyu, Hunter Song, Ji Liu, Peng Wu, Zheqing Zhu

CoRR, 2024

Exploiting Structure in Offline Multi-Agent RL: The Benefits of Low Interaction Rank.

Wenhao Zhan, Scott Fujimoto, Zheqing Zhu, Jason D. Lee, Daniel R. Jiang, Yonathan Efroni

CoRR, 2024

Uncertainty of Joint Neural Contextual Bandit.

Hongbo Guo, Zheqing Zhu

CoRR, 2024

Offline Reinforcement Learning for Optimizing Production Bidding Policies.

Dmytro Korenkevych, Frank Cheng, Artsiom Balakir, Alex Nikulkov, Lingnan Gao, Zhihao Cen, Zuobing Xu, Zheqing Zhu

Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024

IQL-TD-MPC: Implicit Q-Learning for Hierarchical Model Predictive Control.

Rohan Chitnis, Yingchen Xu, Bobak Hashemi, Lucas Lehnert, Ürün Dogan, Zheqing Zhu, Olivier Delalleau

Proceedings of the IEEE International Conference on Robotics and Automation, 2024

2023

Pearl: A Production-ready Reinforcement Learning Agent.

Zheqing Zhu, Rodrigo de Salvo Braz, Jalaj Bhandari, Daniel Jiang, Yi Wan, Yonathan Efroni, Liyuan Wang, Ruiyang Xu, Hongbo Guo, Alex Nikulkov, Dmytro Korenkevych, Ürün Dogan, Frank Cheng, Zheng Wu, Wanqiao Xu

CoRR, 2023

Non-Stationary Contextual Bandit Learning via Neural Predictive Ensemble Sampling.

Zheqing Zhu, Yueyang Liu, Xu Kuang, Benjamin Van Roy

CoRR, 2023

Two-tiered Online Optimization of Region-wide Datacenter Resource Allocation via Deep Reinforcement Learning.

Chang-Lin Chen, Hanhan Zhou, Jiayu Chen, Mohammad Pedramfar, Vaneet Aggarwal, Tian Lan, Zheqing Zhu, Chi Zhou, Tim Gasser, Pol Mauri Ruiz, Vijay Menon, Neeraj Kumar, Hongbo Dong

CoRR, 2023

Optimism Based Exploration in Large-Scale Recommender Systems.

Hongbo Guo, Ruben Naeff, Alex Nikulkov, Zheqing Zhu

CoRR, 2023

Deep Exploration for Recommendation Systems.

Zheqing Zhu, Benjamin Van Roy

Proceedings of the 17th ACM Conference on Recommender Systems, 2023

Optimizing Long-term Value for Auction-Based Recommender Systems via On-Policy Reinforcement Learning.

Ruiyang Xu, Jalaj Bhandari, Dmytro Korenkevych, Fan Liu, Yuchen He, Alex Nikulkov, Zheqing Zhu

Proceedings of the 17th ACM Conference on Recommender Systems, 2023

Scalable Neural Contextual Bandit for Recommender Systems.

Zheqing Zhu, Benjamin Van Roy

Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023

2020

Multi-Agent Safe Planning with Gaussian Processes.

Zheqing Zhu, Erdem Biyik, Dorsa Sadigh

Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2020

2017

A Modified Levy Jump-Diffusion Model Based on Market Sentiment Memory for Online Jump Prediction.

Zheqing Zhu, Jian-Guo Liu, Lei Li

CoRR, 2017