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Zehong Hu
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2020 – today
- 2023
- [j6]Long Yang
, Zhao Li
A Thompson Sampling Algorithm With Logarithmic Regret for Unimodal Gaussian Bandit. IEEE Trans. Neural Networks Learn. Syst. 34(9): 5332-5341 (2023) - [j5]Zhao Li
Noah: Reinforcement-Learning-Based Rate Limiter for Microservices in Large-Scale E-Commerce Services. IEEE Trans. Neural Networks Learn. Syst. 34(9): 5403-5417 (2023) - [c15]Huizhong Guo, Jinfeng Li, Jingyi Wang, Xiangyu Liu, Dongxia Wang, Zehong Hu, Rong Zhang, Hui Xue:
FairRec: Fairness Testing for Deep Recommender Systems. ISSTA 2023: 310-321 - [i4]Huizhong Guo, Jinfeng Li, Jingyi Wang, Xiangyu Liu, Dongxia Wang, Zehong Hu, Rong Zhang, Hui Xue:
FairRec: Fairness Testing for Deep Recommender Systems. CoRR abs/2304.07030 (2023) - 2022
- [j4]Zhao Li
Constrained Dual-Level Bandit for Personalized Impression Regulation in Online Ranking Systems. ACM Trans. Knowl. Discov. Data 16(2): 23:1-23:23 (2022) - 2021
- [j3]Junshuai Song, Xiaoru Qu
A subgraph-based knowledge reasoning method for collective fraud detection in E-commerce. Neurocomputing 461: 587-597 (2021) - [c14]Haishuai Wang, Zhao Li, Xuanwu Liu, Donghui Ding, Zehong Hu, Peng Zhang, Chuan Zhou, Jiajun Bu:
Fulfillment-Time-Aware Personalized Ranking for On-Demand Food Recommendation. CIKM 2021: 4184-4192 - 2020
- [c13]Zhao Li
Attention with Long-Term Interval-Based Gated Recurrent Units for Modeling Sequential User Behaviors. DASFAA (1) 2020: 663-670 - [c12]Junshuai Song, Zhao Li
PoisonRec: An Adaptive Data Poisoning Framework for Attacking Black-box Recommender Systems. ICDE 2020: 157-168
2010 – 2019
- 2019
- [j2]Zining Liu
Which Channel to Ask My Question?: Personalized Customer Service Request Stream Routing Using Deep Reinforcement Learning. IEEE Access 7: 107744-107756 (2019) - [c11]Zehong Hu, Jie Zhang, Zhao Li:
General Robustness Evaluation of Incentive Mechanism against Bounded Rationality Using Continuum-Armed Bandits. AAAI 2019: 6070-6078 - [c10]Zehong Hu, Zhen Wang, Zhao Li, Shichang Hu, Shasha Ruan, Jie Zhang:
Fraud Regulating Policy for E-Commerce via Constrained Contextual Bandits. AAMAS 2019: 1377-1385 - [c9]Zhao Li
FAIR: Fraud Aware Impression Regulation System in Large-Scale Real-Time E-Commerce Search Platform. ICDE 2019: 1898-1903 - [c8]Chong Long, Zining Liu, Xiaolu Lu, Zehong Hu, Yafang Wang:
CRSRL: Customer Routing System Using Reinforcement Learning. IJCAI 2019: 6548-6550 - [i3]Lukasz Kidzinski, Carmichael F. Ong, Sharada Prasanna Mohanty, Jennifer L. Hicks, Sean F. Carroll, Bo Zhou, Hong-cheng Zeng, Fan Wang, Rongzhong Lian, Hao Tian, Wojciech Jaskowski, Garrett Andersen, Odd Rune Lykkebø, Nihat Engin Toklu, Pranav Shyam, Rupesh Kumar Srivastava, Sergey Kolesnikov, Oleksii Hrinchuk, Anton Pechenko, Mattias Ljungström, Zhen Wang, Xu Hu, Zehong Hu, Minghui Qiu, Jun Huang, Aleksei Shpilman, Ivan Sosin, Oleg Svidchenko, Aleksandra Malysheva, Daniel Kudenko, Lance Rane, Aditya Bhatt, Zhengfei Wang, Penghui Qi, Zeyang Yu, Peng Peng, Quan Yuan, Wenxin Li, Yunsheng Tian, Ruihan Yang, Pingchuan Ma, Shauharda Khadka, Somdeb Majumdar, Zach Dwiel, Yinyin Liu, Evren Tumer, Jeremy D. Watson, Marcel Salathé, Sergey Levine, Scott L. Delp:
Artificial Intelligence for Prosthetics - challenge solutions. CoRR abs/1902.02441 (2019) - [i2]Zining Liu, Chong Long, Xiaolu Lu, Zehong Hu, Jie Zhang, Yafang Wang:
Which Channel to Ask My Question? Personalized Customer Service RequestStream Routing using DeepReinforcement Learning. CoRR abs/1911.10521 (2019) - 2018
- [b1]Zehong Hu:
Learning-based mechanism design for microtask crowdsourcing. Nanyang Technological University, Singapore, 2018 - [j1]Zehong Hu
Toward General Robustness Evaluation of Incentive Mechanism Against Bounded Rationality. IEEE Trans. Comput. Soc. Syst. 5(3): 698-712 (2018) - [c7]Robin Cohen, Peng-Fei Wang, Zehong Hu:
Revisiting Public Reputation Calculation in a Personalized Trust Model. TRUST@AAMAS 2018: 13-24 - [c6]Zehong Hu, Jie Zhang:
A Novel Strategy for Active Task Assignment in Crowd Labeling. IJCAI 2018: 1538-1545 - [c5]Zehong Hu, Yitao Liang, Jie Zhang, Zhao Li, Yang Liu:
Inference Aided Reinforcement Learning for Incentive Mechanism Design in Crowdsourcing. NeurIPS 2018: 5512-5522 - [i1]Zehong Hu, Yitao Liang, Yang Liu, Jie Zhang:
Inference Aided Reinforcement Learning for Incentive Mechanism Design in Crowdsourcing. CoRR abs/1806.00206 (2018) - 2017
- [c4]Donghun Kang, Zhenchao C. Bing, Wen Song, Zehong Hu, Shuo Chen, Jie Zhang, Hui Xi:
Automatic Construction of Agent-based Simulation Using Business Process Diagrams and Ontology-based Models. AAMAS 2017: 1793-1795 - [c3]Zehong Hu, Jie Zhang:
Optimal Posted-Price Mechanism in Microtask Crowdsourcing. IJCAI 2017: 228-234 - 2016
- [c2]Zehong Hu, Meng Sha, Moath H. A. Jarrah, Jie Zhang, Hui Xi:
Efficient Computation of Emergent Equilibrium in Agent-Based Simulation. AAAI 2016: 2501-2508 - [c1]Zehong Hu:
A Novel Approach to Evaluate Robustness of Incentive Mechanism Against Bounded Rationality: (Doctoral Consortium). AAMAS 2016: 1522-1523
Coauthor Index
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