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ORCIDPeng Zhao 0006
Person information
- affiliation: Nanjing University, National Key Laboratory for Novel Software Technology, Cjina
Other persons with the same name
- Peng Zhao — disambiguation page
- Peng Zhao 0001
![[0000-0001-7033-9315]](https://dblp.uni-trier.de/img/orcid-mark.12x12.png "0000-0001-7033-9315")
— Xi'an Jiaotong University, Department of Computer Science and Technology, China - Peng Zhao 0002 — Huazhong University of Science and Technology, School of Management / School of Automation, Wuhan, China
- Peng Zhao 0003 — Hangzhou Dianzi University, MOE, Key Lab of RF Circuits and Systems, Microelectronics CAD Center, China (and 1 more)
- Peng Zhao 0004 — University of Georgia, Department of Biochemistry and Molecular Biology, Athens, GA, USA
- Peng Zhao 0005 — Arizona State University, School for Engineering of Matter, Transport & Energy, Tempe, AZ, USA (and 1 more)
- Peng Zhao 0007 — University of Missouri, Informatics Institute, Columbia, MO, USA
- Peng Zhao 0008 — Huawei Technology Co. Ltd, Beijing, China (and 2 more)
- Peng Zhao 0009 — University of Plymouth, School of Engineering, Computing and Mathematics, UK
- Peng Zhao 0010 — Anhui University, School of Computer Science and Technology, China
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Journal Articles
- 2024
[j10]Peng Zhao, Jia-Wei Shan, Yu-Jie Zhang, Zhi-Hua Zhou:
Exploratory machine learning with unknown unknowns. Artif. Intell. 327: 104059 (2024)- [j9]Peng Zhao, Yu-Jie Zhang, Lijun Zhang, Zhi-Hua Zhou:
Adaptivity and Non-stationarity: Problem-dependent Dynamic Regret for Online Convex Optimization. J. Mach. Learn. Res. 25: 98:1-98:52 (2024) - [j8]Sijia Chen, Yu-Jie Zhang, Wei-Wei Tu, Peng Zhao, Lijun Zhang:
Optimistic Online Mirror Descent for Bridging Stochastic and Adversarial Online Convex Optimization. J. Mach. Learn. Res. 25: 178:1-178:62 (2024) - 2023
- [j7]Peng Zhao, Yu-Hu Yan, Yu-Xiang Wang, Zhi-Hua Zhou:
Non-stationary Online Learning with Memory and Non-stochastic Control. J. Mach. Learn. Res. 24: 206:1-206:70 (2023) - [j6]Yu-Hu Yan, Peng Zhao, Zhi-Hua Zhou:
Online Non-stochastic Control with Partial Feedback. J. Mach. Learn. Res. 24: 273:1-273:50 (2023) - 2022
- [j5]Ming Pang, Kai Ming Ting, Peng Zhao, Zhi-Hua Zhou:
Improving Deep Forest by Screening. IEEE Trans. Knowl. Data Eng. 34(9): 4298-4312 (2022) - [j4]Zhen-Yu Zhang, Peng Zhao, Yuan Jiang, Zhi-Hua Zhou:
Learning From Incomplete and Inaccurate Supervision. IEEE Trans. Knowl. Data Eng. 34(12): 5854-5868 (2022) - 2021
- [j3]Peng Zhao, Guanghui Wang, Lijun Zhang, Zhi-Hua Zhou:
Bandit Convex Optimization in Non-stationary Environments. J. Mach. Learn. Res. 22: 125:1-125:45 (2021) - [j2]Peng Zhao, Xinqiang Wang, Siyu Xie, Lei Guo, Zhi-Hua Zhou:
Distribution-Free One-Pass Learning. IEEE Trans. Knowl. Data Eng. 33(3): 951-963 (2021) - 2020
- [j1]Peng Zhao, Le-Wen Cai, Zhi-Hua Zhou:
Handling concept drift via model reuse. Mach. Learn. 109(3): 533-568 (2020)
Conference and Workshop Papers
- 2024
- [c36]Long-Fei Li, Peng Zhao, Zhi-Hua Zhou:
Dynamic Regret of Adversarial MDPs with Unknown Transition and Linear Function Approximation. AAAI 2024: 13572-13580 - [c35]Long-Fei Li, Peng Zhao, Zhi-Hua Zhou:
Improved Algorithm for Adversarial Linear Mixture MDPs with Bandit Feedback and Unknown Transition. AISTATS 2024: 3061-3069 - [c34]Yuyang Qian, Peng Zhao, Yu-Jie Zhang, Masashi Sugiyama, Zhi-Hua Zhou:
Efficient Non-stationary Online Learning by Wavelets with Applications to Online Distribution Shift Adaptation. ICML 2024 - [c33]Jing Wang, Miao Yu, Peng Zhao, Zhi-Hua Zhou:
Learning with Adaptive Resource Allocation. ICML 2024 - [c32]Yu-Hu Yan, Jing Wang, Peng Zhao:
Handling Heterogeneous Curvatures in Bandit LQR Control. ICML 2024 - 2023
- [c31]Jing Wang, Peng Zhao, Zhi-Hua Zhou:
Revisiting Weighted Strategy for Non-stationary Parametric Bandits. AISTATS 2023: 7913-7942 - [c30]Jia-Wei Shan, Peng Zhao, Zhi-Hua Zhou:
Beyond Performative Prediction: Open-environment Learning with Presence of Corruptions. AISTATS 2023: 7981-7998 - [c29]Yuyang Qian, Yong Bai, Zhen-Yu Zhang, Peng Zhao, Zhi-Hua Zhou:
Handling New Class in Online Label Shift. ICDM 2023: 1283-1288 - [c28]Sijia Chen, Wei-Wei Tu, Peng Zhao, Lijun Zhang:
Optimistic Online Mirror Descent for Bridging Stochastic and Adversarial Online Convex Optimization. ICML 2023: 5002-5035 - [c27]Yu-Hu Yan, Peng Zhao, Zhi-Hua Zhou:
Fast Rates in Time-Varying Strongly Monotone Games. ICML 2023: 39138-39164 - [c26]Lijun Zhang, Peng Zhao, Zhen-Hua Zhuang, Tianbao Yang, Zhi-Hua Zhou:
Stochastic Approximation Approaches to Group Distributionally Robust Optimization. NeurIPS 2023 - [c25]Long-Fei Li, Peng Zhao, Zhi-Hua Zhou:
Dynamic Regret of Adversarial Linear Mixture MDPs. NeurIPS 2023 - [c24]Yu-Hu Yan, Peng Zhao, Zhi-Hua Zhou:
Universal Online Learning with Gradient Variations: A Multi-layer Online Ensemble Approach. NeurIPS 2023 - 2022
- [c23]Peng Zhao, Yu-Xiang Wang, Zhi-Hua Zhou:
Non-stationary Online Learning with Memory and Non-stochastic Control. AISTATS 2022: 2101-2133 - [c22]Haipeng Luo, Mengxiao Zhang, Peng Zhao:
Adaptive Bandit Convex Optimization with Heterogeneous Curvature. COLT 2022: 1576-1612 - [c21]Haipeng Luo, Mengxiao Zhang, Peng Zhao, Zhi-Hua Zhou:
Corralling a Larger Band of Bandits: A Case Study on Switching Regret for Linear Bandits. COLT 2022: 3635-3684 - [c20]Mengxiao Zhang, Peng Zhao, Haipeng Luo, Zhi-Hua Zhou:
No-Regret Learning in Time-Varying Zero-Sum Games. ICML 2022: 26772-26808 - [c19]Peng Zhao, Longfei Li, Zhi-Hua Zhou:
Dynamic Regret of Online Markov Decision Processes. ICML 2022: 26865-26894 - [c18]Peng Zhao, Yan-Feng Xie, Lijun Zhang, Zhi-Hua Zhou:
Efficient Methods for Non-stationary Online Learning. NeurIPS 2022 - [c17]Yong Bai, Yu-Jie Zhang, Peng Zhao, Masashi Sugiyama, Zhi-Hua Zhou:
Adapting to Online Label Shift with Provable Guarantees. NeurIPS 2022 - 2021
- [c16]Bo-Jian Hou, Yu-Hu Yan, Peng Zhao, Zhi-Hua Zhou:
Storage Fit Learning with Feature Evolvable Streams. AAAI 2021: 7729-7736 - [c15]Yu-Jie Zhang, Yu-Hu Yan, Peng Zhao, Zhi-Hua Zhou:
Towards Enabling Learnware to Handle Unseen Jobs. AAAI 2021: 10964-10972 - [c14]Peng Zhao, Yu-Jie Zhang, Zhi-Hua Zhou:
Exploratory Machine Learning with Unknown Unknowns. AAAI 2021: 10999-11006 - [c13]Peng Zhao, Lijun Zhang:
Improved Analysis for Dynamic Regret of Strongly Convex and Smooth Functions. L4DC 2021: 48-59 - 2020
- [c12]Peng Zhao, Lijun Zhang, Yuan Jiang, Zhi-Hua Zhou:
A Simple Approach for Non-stationary Linear Bandits. AISTATS 2020: 746-755 - [c11]Peng Zhao, Guanghui Wang, Lijun Zhang, Zhi-Hua Zhou:
Bandit Convex Optimization in Non-stationary Environments. AISTATS 2020: 1508-1518 - [c10]Zhenyu Zhang, Peng Zhao, Yuan Jiang, Zhi-Hua Zhou:
Learning with Feature and Distribution Evolvable Streams. ICML 2020: 11317-11327 - [c9]Peng Zhao, Yu-Jie Zhang, Lijun Zhang, Zhi-Hua Zhou:
Dynamic Regret of Convex and Smooth Functions. NeurIPS 2020 - [c8]Yu-Jie Zhang, Peng Zhao, Lanjihong Ma, Zhi-Hua Zhou:
An Unbiased Risk Estimator for Learning with Augmented Classes. NeurIPS 2020 - [c7]Yu-Jie Zhang, Peng Zhao, Zhi-Hua Zhou:
A Simple Online Algorithm for Competing with Dynamic Comparators. UAI 2020: 390-399 - 2019
- [c6]Xin-Qiang Cai, Peng Zhao, Kai-Ming Ting, Xin Mu, Yuan Jiang:
Nearest Neighbor Ensembles: An Effective Method for Difficult Problems in Streaming Classification with Emerging New Classes. ICDM 2019: 970-975 - [c5]Zhenyu Zhang, Peng Zhao, Yuan Jiang, Zhi-Hua Zhou:
Learning from Incomplete and Inaccurate Supervision. KDD 2019: 1017-1025 - 2018
- [c4]Chong Liu, Peng Zhao, Sheng-Jun Huang, Yuan Jiang, Zhi-Hua Zhou:
Dual Set Multi-Label Learning. AAAI 2018: 3635-3642 - [c3]Peng Zhao, Zhi-Hua Zhou:
Label Distribution Learning by Optimal Transport. AAAI 2018: 4506-4513 - [c2]Ming Pang, Kai-Ming Ting, Peng Zhao, Zhi-Hua Zhou:
Improving Deep Forest by Confidence Screening. ICDM 2018: 1194-1199 - 2017
- [c1]Peng Zhao, Yuan Jiang, Zhi-Hua Zhou:
Multi-View Matrix Completion for Clustering with Side Information. PAKDD (2) 2017: 403-415
Informal and Other Publications
- 2024
- [i25]Long-Fei Li, Peng Zhao, Zhi-Hua Zhou:
Improved Algorithm for Adversarial Linear Mixture MDPs with Bandit Feedback and Unknown Transition. CoRR abs/2403.04568 (2024) - [i24]Long-Fei Li, Yu-Jie Zhang, Peng Zhao, Zhi-Hua Zhou:
Provably Efficient Reinforcement Learning with Multinomial Logit Function Approximation. CoRR abs/2405.17061 (2024) - [i23]Wenhao Yang, Yibo Wang, Peng Zhao, Lijun Zhang:
Universal Online Convex Optimization with 1 Projection per Round. CoRR abs/2405.19705 (2024) - 2023
- [i22]Yu-Jie Zhang, Zhen-Yu Zhang, Peng Zhao, Masashi Sugiyama:
Adapting to Continuous Covariate Shift via Online Density Ratio Estimation. CoRR abs/2302.02552 (2023) - [i21]Sijia Chen, Wei-Wei Tu, Peng Zhao, Lijun Zhang:
Optimistic Online Mirror Descent for Bridging Stochastic and Adversarial Online Convex Optimization. CoRR abs/2302.04552 (2023) - [i20]Lijun Zhang, Peng Zhao, Tianbao Yang, Zhi-Hua Zhou:
Stochastic Approximation Approaches to Group Distributionally Robust Optimization. CoRR abs/2302.09267 (2023) - [i19]Jing Wang, Peng Zhao, Zhi-Hua Zhou:
Revisiting Weighted Strategy for Non-stationary Parametric Bandits. CoRR abs/2303.02691 (2023) - [i18]Yu-Hu Yan, Peng Zhao, Zhi-Hua Zhou:
Universal Online Learning with Gradual Variations: A Multi-layer Online Ensemble Approach. CoRR abs/2307.08360 (2023) - [i17]Peng Zhao, Yan-Feng Xie, Lijun Zhang, Zhi-Hua Zhou:
Efficient Methods for Non-stationary Online Learning. CoRR abs/2309.08911 (2023) - 2022
- [i16]Mengxiao Zhang, Peng Zhao, Haipeng Luo, Zhi-Hua Zhou:
No-Regret Learning in Time-Varying Zero-Sum Games. CoRR abs/2201.12736 (2022) - [i15]Haipeng Luo, Mengxiao Zhang, Peng Zhao:
Adaptive Bandit Convex Optimization with Heterogeneous Curvature. CoRR abs/2202.06150 (2022) - [i14]Haipeng Luo, Mengxiao Zhang, Peng Zhao, Zhi-Hua Zhou:
Corralling a Larger Band of Bandits: A Case Study on Switching Regret for Linear Bandits. CoRR abs/2202.06151 (2022) - [i13]Yong Bai, Yu-Jie Zhang, Peng Zhao, Masashi Sugiyama, Zhi-Hua Zhou:
Adapting to Online Label Shift with Provable Guarantees. CoRR abs/2207.02121 (2022) - [i12]Peng Zhao, Longfei Li, Zhi-Hua Zhou:
Dynamic Regret of Online Markov Decision Processes. CoRR abs/2208.12483 (2022) - 2021
- [i11]Peng Zhao, Yu-Xiang Wang, Zhi-Hua Zhou:
Non-stationary Online Learning with Memory and Non-stochastic Control. CoRR abs/2102.03758 (2021) - [i10]Peng Zhao, Lijun Zhang:
Non-stationary Linear Bandits Revisited. CoRR abs/2103.05324 (2021) - [i9]Peng Zhao, Yu-Jie Zhang, Lijun Zhang, Zhi-Hua Zhou:
Adaptivity and Non-stationarity: Problem-dependent Dynamic Regret for Online Convex Optimization. CoRR abs/2112.14368 (2021) - 2020
- [i8]Yu-Jie Zhang, Peng Zhao, Zhi-Hua Zhou:
Exploratory Machine Learning with Unknown Unknowns. CoRR abs/2002.01605 (2020) - [i7]Peng Zhao, Lijun Zhang:
Improved Analysis for Dynamic Regret of Strongly Convex and Smooth Functions. CoRR abs/2006.05876 (2020) - [i6]Peng Zhao, Yu-Jie Zhang, Lijun Zhang, Zhi-Hua Zhou:
Dynamic Regret of Convex and Smooth Functions. CoRR abs/2007.03479 (2020) - [i5]Bo-Jian Hou, Yu-Hu Yan, Peng Zhao, Zhi-Hua Zhou:
Storage Fit Learning with Feature Evolvable Streams. CoRR abs/2007.11280 (2020) - 2019
- [i4]Peng Zhao, Guanghui Wang, Lijun Zhang, Zhi-Hua Zhou:
Bandit Convex Optimization in Non-stationary Environments. CoRR abs/1907.12340 (2019) - [i3]Yu-Jie Zhang, Peng Zhao, Zhi-Hua Zhou:
An Unbiased Risk Estimator for Learning with Augmented Classes. CoRR abs/1910.09388 (2019) - 2018
- [i2]Peng Zhao, Le-Wen Cai, Zhi-Hua Zhou:
Handling Concept Drift via Model Reuse. CoRR abs/1809.02804 (2018) - 2017
- [i1]Peng Zhao, Zhi-Hua Zhou:
Distribution-Free One-Pass Learning. CoRR abs/1706.02471 (2017)
Coauthor Index
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