Zheqing Zhu

Publication Activity (10 Years)

Years Active: 2017-2024
Publications (10 Years): 20

Top Topics

Upper Confidence Bound

Reinforcement Learning

Exploration Exploitation Tradeoff

Gaussian Process

Top Venues

Publications

Dmytro Korenkevych, Frank Cheng, Artsiom Balakir, Alex Nikulkov, Lingnan Gao, Zhihao Cen, Zuobing Xu, Zheqing Zhu
Offline Reinforcement Learning for Optimizing Production Bidding Policies. KDD (2024)
Rohan Chitnis, Yingchen Xu, Bobak Hashemi, Lucas Lehnert, Ürün Dogan, Zheqing Zhu, Olivier Delalleau
IQL-TD-MPC: Implicit Q-Learning for Hierarchical Model Predictive Control. ICRA (2024)
Geng Ji, Wentao Jiang, Jiang Li, Fahmid Morshed Fahid, Zhengxing Chen, Yinghua Li, Jun Xiao, Chongxi Bao, Zheqing Zhu
Learning to bid and rank together in recommendation systems. Mach. Learn. 113 (5) (2024)
Hongbo Guo, Zheqing Zhu
Uncertainty of Joint Neural Contextual Bandit. CoRR (2024)
Geng Ji, Wentao Jiang, Jiang Li, Fahmid Morshed Fahid, Zhengxing Chen, Yinghua Li, Jun Xiao, Chongxi Bao, Zheqing Zhu
Correction to: Learning to bid and rank together in recommendation systems. Mach. Learn. 113 (3) (2024)
Zheqing Zhu, Yueyang Liu, Xu Kuang, Benjamin Van Roy
Non-Stationary Contextual Bandit Learning via Neural Predictive Ensemble Sampling. CoRR (2023)
Ruiyang Xu, Jalaj Bhandari, Dmytro Korenkevych, Fan Liu, Yuchen He, Alex Nikulkov, Zheqing Zhu
Optimizing Long-term Value for Auction-Based Recommender Systems via On-Policy Reinforcement Learning. RecSys (2023)
Ruiyang Xu, Jalaj Bhandari, Dmytro Korenkevych, Fan Liu, Yuchen He, Alex Nikulkov, Zheqing Zhu
Optimizing Long-term Value for Auction-Based Recommender Systems via On-Policy Reinforcement Learning. CoRR (2023)
Zheqing Zhu, Benjamin Van Roy
Scalable Neural Contextual Bandit for Recommender Systems. CoRR (2023)
Hongbo Guo, Ruben Naeff, Alex Nikulkov, Zheqing Zhu
Optimism Based Exploration in Large-Scale Recommender Systems. CoRR (2023)
Rohan Chitnis, Yingchen Xu, Bobak Hashemi, Lucas Lehnert, Urun Dogan, Zheqing Zhu, Olivier Delalleau
IQL-TD-MPC: Implicit Q-Learning for Hierarchical Model Predictive Control. CoRR (2023)
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
Two-tiered Online Optimization of Region-wide Datacenter Resource Allocation via Deep Reinforcement Learning. CoRR (2023)
Zheqing Zhu, Benjamin Van Roy
Deep Exploration for Recommendation Systems. RecSys (2023)
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
Pearl: A Production-ready Reinforcement Learning Agent. CoRR (2023)
Zheqing Zhu, Benjamin Van Roy
Scalable Neural Contextual Bandit for Recommender Systems. CIKM (2023)
Dmytro Korenkevych, Frank Cheng, Artsiom Balakir, Alex Nikulkov, Lingnan Gao, Zhihao Cen, Zuobing Xu, Zheqing Zhu
Offline Reinforcement Learning for Optimizing Production Bidding Policies. CoRR (2023)
Zheqing Zhu, Benjamin Van Roy
Deep Exploration for Recommendation Systems. CoRR (2021)
Zheqing Zhu, Erdem Biyik, Dorsa Sadigh
Multi-Agent Safe Planning with Gaussian Processes. IROS (2020)
Zheqing Zhu, Erdem Biyik, Dorsa Sadigh
Multi-Agent Safe Planning with Gaussian Processes. CoRR (2020)
Zheqing Zhu, Jian-Guo Liu, Lei Li
A Modified Levy Jump-Diffusion Model Based on Market Sentiment Memory for Online Jump Prediction. CoRR (2017)