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2020 – today
- 2024
[j2]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): 1509 (2024)- [j1]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): 2559-2573 (2024) - [c6]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: 9154-9160 - [c5]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: 5251-5259 - [i13]Hongbo Guo, Zheqing Zhu:
Uncertainty of Joint Neural Contextual Bandit. CoRR abs/2406.02515 (2024) - [i12]Wenhao Zhan, Scott Fujimoto, Zheqing Zhu, Jason D. Lee, Daniel R. Jiang, Yonathan Efroni:
Exploiting Structure in Offline Multi-Agent RL: The Benefits of Low Interaction Rank. CoRR abs/2410.01101 (2024) - 2023
- [c4]Zheqing Zhu, Benjamin Van Roy:
Scalable Neural Contextual Bandit for Recommender Systems. CIKM 2023: 3636-3646 - [c3]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: 955-962 - [c2]Zheqing Zhu, Benjamin Van Roy:
Deep Exploration for Recommendation Systems. RecSys 2023: 963-970 - [i11]Hongbo Guo, Ruben Naeff, Alex Nikulkov, Zheqing Zhu:
Optimism Based Exploration in Large-Scale Recommender Systems. CoRR abs/2304.02572 (2023) - [i10]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 abs/2305.13747 (2023) - [i9]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. CoRR abs/2306.00867 (2023) - [i8]Zheqing Zhu, Benjamin Van Roy:
Scalable Neural Contextual Bandit for Recommender Systems. CoRR abs/2306.14834 (2023) - [i7]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 abs/2306.17054 (2023) - [i6]Zheqing Zhu, Yueyang Liu, Xu Kuang, Benjamin Van Roy:
Non-Stationary Contextual Bandit Learning via Neural Predictive Ensemble Sampling. CoRR abs/2310.07786 (2023) - [i5]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 abs/2310.09426 (2023) - [i4]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 abs/2312.03814 (2023) - 2021
- [i3]Zheqing Zhu, Benjamin Van Roy:
Deep Exploration for Recommendation Systems. CoRR abs/2109.12509 (2021) - 2020
- [c1]Zheqing Zhu, Erdem Biyik, Dorsa Sadigh:
Multi-Agent Safe Planning with Gaussian Processes. IROS 2020: 6260-6267 - [i2]Zheqing Zhu, Erdem Biyik, Dorsa Sadigh:
Multi-Agent Safe Planning with Gaussian Processes. CoRR abs/2008.04452 (2020)
2010 – 2019
- 2017
- [i1]Zheqing Zhu, Jian-Guo Liu, Lei Li:
A Modified Levy Jump-Diffusion Model Based on Market Sentiment Memory for Online Jump Prediction. CoRR abs/1709.03611 (2017)
Coauthor Index
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