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ORCIDYao Zhou 0003
Person information
- affiliation: University of Illinois Urbana-Champaign, Urbana, IL, USA
Other persons with the same name
- Yao Zhou — disambiguation page
- Yao Zhou 0001
![[0000-0001-9791-7664]](https://dblp.uni-trier.de/img/orcid-mark.12x12.png "0000-0001-9791-7664")
— Institute of Botany, Beijing, China - Yao Zhou 0002 — Sichuan University, Chengdu, Sichuan, China
- Yao Zhou 0004 — Shanghai Jiao Tong University, Shanghai, China
- Yao Zhou 0005 — Tianjin Medical University, Tianjin, China
- Yao Zhou 0006 — Nanjing University of Information Science and Technology, Nanjing, China
- Yao Zhou 0007 — Embry-Riddle Aeronautical University, Daytona, FL, USA
- Yao Zhou 0008 — University of Electronic Science and Technology of China, Chengdu, China
- Yao Zhou 0009 — Institute of Software, Chinese Academy of Sciences, Beijing, China
- Yao Zhou 0010 — Jiangnan University, Wuxi, China
- Yao Zhou 0011 — Tencent, Shenzhen, China
- Yao Zhou 0012 — Wuhan University of Technology, Wuhan, Hubei, China
- Yao Zhou 0013 — Southwest Jiaotong University, Chengdu, China
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2020 – today
- 2026
[j4]Yunzhe Qi, Yao Zhou, Yikun Ban, Allan Stewart, Chuanwei Ruan, Jiachuan He, Shishir Kumar Prasad, Haixun Wang, Jingrui He:
Bi-level Hierarchical Neural Contextual Bandits for Online Recommendation. Trans. Mach. Learn. Res. 2026 (2026)- [i8]Longfeng Wu, Yao Zhou, Tong Zeng, Zhimin Peng, Bhanu Pratap Singh Rawat, Lecheng Zheng, Giovanni Seni, Dawei Zhou:
Bi-NAS: Towards Effective and Personalized Explanation for Recommender Systems via Bi-Level Neural Architecture Search. CoRR abs/2607.01387 (2026) - 2025
- [j3]Yao Zhou, Haonan Wang, Jingrui He, Haixun Wang:
Review-Based Explainable Recommendations: A Transparency Perspective. Trans. Recomm. Syst. 3(3): 34:1-34:20 (2025) - [c13]Longfeng Wu, Yao Zhou, Tong Zeng, Zhimin Peng, Bhanu Pratap Singh Rawat, Lecheng Zheng, Giovanni Seni, Dawei Zhou:
Bi-NAS: Towards Effective and Personalized Explanation for Recommender Systems via Bi-Level Neural Architecture Search. ICDM 2025: 1642-1651 - [c12]Gyuseok Lee, Yaochen Zhu, Hwanjo Yu, Yao Zhou, Jundong Li:
Collaborative Diffusion Model for Recommender System. WWW (Companion Volume) 2025: 1091-1095 - [c11]Longfeng Wu, Yao Zhou, Jian Kang, Dawei Zhou:
Bridging Fairness and Uncertainty: Theoretical Insights and Practical Strategies for Equalized Coverage in GNNs. WWW 2025: 4625-4634 - [i7]Gyuseok Lee, Yaochen Zhu, Hwanjo Yu, Yao Zhou, Jundong Li:
Collaborative Diffusion Model for Recommender System. CoRR abs/2501.18997 (2025) - 2023
- [j2]Liwei Che, Jiaqi Wang, Yao Zhou, Fenglong Ma:
Multimodal Federated Learning: A Survey. Sensors 23(15): 6986 (2023) - 2022
- [c10]Yao Zhou, Jun Wu, Haixun Wang, Jingrui He:
Adversarial Robustness through Bias Variance Decomposition: A New Perspective for Federated Learning. CIKM 2022: 2753-2762 - [c9]Longfeng Wu, Yao Zhou, Dawei Zhou:
Towards High-Order Complementary Recommendation via Logical Reasoning Network. ICDM 2022: 1227-1232 - [i6]Longfeng Wu, Yao Zhou, Dawei Zhou:
Towards High-Order Complementary Recommendation via Logical Reasoning Network. CoRR abs/2212.04966 (2022) - 2021
- [c8]Yao Zhou, Jianpeng Xu, Jun Wu, Zeinab Taghavi Nasrabadi, Evren Körpeoglu, Kannan Achan, Jingrui He:
PURE: Positive-Unlabeled Recommendation with Generative Adversarial Network. KDD 2021: 2409-2419 - [i5]Yao Zhou, Haonan Wang, Jingrui He, Haixun Wang:
From Intrinsic to Counterfactual: On the Explainability of Contextualized Recommender Systems. CoRR abs/2110.14844 (2021) - 2020
- [c7]Yao Zhou, Arun Reddy Nelakurthi, Ross Maciejewski, Wei Fan, Jingrui He:
Crowd Teaching with Imperfect Labels. WWW 2020: 110-121 - [i4]Yao Zhou, Jun Wu, Jingrui He:
Robust Decentralized Learning for Neural Networks. CoRR abs/2009.09026 (2020) - [i3]Yao Zhou, Jianpeng Xu, Jun Wu, Zeinab Taghavi Nasrabadi, Evren Körpeoglu, Kannan Achan, Jingrui He:
GAN-based Recommendation with Positive-Unlabeled Sampling. CoRR abs/2012.06901 (2020)
2010 – 2019
- 2019
- [j1]Yao Zhou, Lei Ying, Jingrui He:
Multi-task Crowdsourcing via an Optimization Framework. ACM Trans. Knowl. Discov. Data 13(3): 27:1-27:26 (2019) - [c6]Yao Zhou, Fenglong Ma, Jing Gao, Jingrui He:
Optimizing the Wisdom of the Crowd: Inference, Learning, and Teaching. KDD 2019: 3231-3232 - 2018
- [c5]Yao Zhou, Arun Reddy Nelakurthi, Jingrui He:
Unlearn What You Have Learned: Adaptive Crowd Teaching with Exponentially Decayed Memory Learners. KDD 2018: 2817-2826 - [c4]Pengfei Jiang, Weina Wang, Yao Zhou, Jingrui He, Lei Ying:
A Winners-Take-All Incentive Mechanism for Crowd-Powered Systems. NetEcon@SIGMETRICS 2018: 3:1-3:6 - [i2]Yao Zhou, Arun Reddy Nelakurthi, Jingrui He:
Unlearn What You Have Learned: Adaptive Crowd Teaching with Exponentially Decayed Memory Learners. CoRR abs/1804.06481 (2018) - [i1]Yao Zhou, Jingrui He:
Optimizing the Wisdom of the Crowd: Inference, Learning, and Teaching. CoRR abs/1806.09018 (2018) - 2017
- [c3]Yao Zhou, Jingrui He:
A Randomized Approach for Crowdsourcing in the Presence of Multiple Views. ICDM 2017: 685-694 - [c2]Yao Zhou, Lei Ying, Jingrui He:
MultiC2: an Optimization Framework for Learning from Task and Worker Dual Heterogeneity. SDM 2017: 579-587 - 2016
- [c1]Yao Zhou, Jingrui He:
Crowdsourcing via Tensor Augmentation and Completion. IJCAI 2016: 2435-2441
Coauthor Index
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last updated on 2026-08-18 01:12 CEST by the dblp team
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