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2020 – today
- 2024
[j31]Zhimei Ren
, Zhengyuan Zhou:
Dynamic Batch Learning in High-Dimensional Sparse Linear Contextual Bandits. Manag. Sci. 70(2): 1315-1342 (2024)- [j30]Ruohan Zhan, Zhimei Ren, Susan Athey, Zhengyuan Zhou:
Policy Learning with Adaptively Collected Data. Manag. Sci. 70(8): 5270-5297 (2024) - [j29]Zhengyuan Zhou, Kai Chen, Dianlin Hu, Huazhong Shu, Gouenou Coatrieux, Jean-Louis Coatrieux, Yang Chen:
Global texture sensitive convolutional transformer for medical image steganalysis. Multim. Syst. 30(3): 155 (2024) - [j28]José H. Blanchet, Renyuan Xu, Zhengyuan Zhou:
Delay-Adaptive Learning in Generalized Linear Contextual Bandits. Math. Oper. Res. 49(1): 326-345 (2024) - [j27]Kai Chen, Zhengyuan Zhou, Yuchen Li, Xu Ji, Jiasong Wu, Jean-Louis Coatrieux, Yang Chen, Gouenou Coatrieux:
RED-Net: Residual and Enhanced Discriminative Network for Image Steganalysis in the Internet of Medical Things and Telemedicine. IEEE J. Biomed. Health Informatics 28(3): 1611-1622 (2024) - [j26]Xiaoqin Zhang, Jingjing Zheng, Li Zhao, Zhengyuan Zhou, Zhouchen Lin:
Tensor Recovery With Weighted Tensor Average Rank. IEEE Trans. Neural Networks Learn. Syst. 35(1): 1142-1156 (2024) - [c66]Ying Jin, Ramki Gummadi, Zhengyuan Zhou, Jose H. Blanchet:
Feasible Q-Learning for Average Reward Reinforcement Learning. AISTATS 2024: 1630-1638 - [c65]Zijian Liu, Zhengyuan Zhou:
Revisiting the Last-Iterate Convergence of Stochastic Gradient Methods. ICLR 2024 - [c64]Junyi Fan, Yuxuan Han, Zijian Liu, Jian-Feng Cai, Yang Wang, Zhengyuan Zhou:
On the Convergence of Projected Bures-Wasserstein Gradient Descent under Euclidean Strong Convexity. ICML 2024 - [c63]Zhipeng Liang, Xiaoteng Ma, José H. Blanchet, Jun Yang, Jiheng Zhang, Zhengyuan Zhou:
Single-Trajectory Distributionally Robust Reinforcement Learning. ICML 2024 - [c62]Zijian Liu, Zhengyuan Zhou:
On the Last-Iterate Convergence of Shuffling Gradient Methods. ICML 2024 - [c61]Jingyuan Wang, Perry Dong, Ying Jin, Ruohan Zhan, Zhengyuan Zhou:
Adaptively Learning to Select-Rank in Online Platforms. ICML 2024 - [i47]Yuxiao Wen, Yanjun Han, Zhengyuan Zhou:
Stochastic contextual bandits with graph feedback: from independence number to MAS number. CoRR abs/2402.18591 (2024) - [i46]Zijian Liu, Zhengyuan Zhou:
On the Last-Iterate Convergence of Shuffling Gradient Methods. CoRR abs/2403.07723 (2024) - [i45]Yu Xia, Sriram Narayanamoorthy, Zhengyuan Zhou, Joshua Mabry:
Simulation-Based Benchmarking of Reinforcement Learning Agents for Personalized Retail Promotions. CoRR abs/2405.10469 (2024) - [i44]Jingyuan Wang, Perry Dong, Ying Jin, Ruohan Zhan, Zhengyuan Zhou:
Adaptively Learning to Select-Rank in Online Platforms. CoRR abs/2406.05017 (2024) - [i43]Shengbo Wang, Nian Si, Jose H. Blanchet, Zhengyuan Zhou:
Statistical Learning of Distributionally Robust Stochastic Control in Continuous State Spaces. CoRR abs/2406.11281 (2024) - 2023
- [j25]Zhengyuan Zhou, Susan Athey, Stefan Wager:
Offline Multi-Action Policy Learning: Generalization and Optimization. Oper. Res. 71(1): 148-183 (2023) - [j24]Zhaonan Qu, Kaixiang Lin, Zhaojian Li, Jiayu Zhou, Zhengyuan Zhou:
A Unified Linear Speedup Analysis of Federated Averaging and Nesterov FedAvg. J. Artif. Intell. Res. 78: 1143-1200 (2023) - [j23]Nian Si, Fan Zhang, Zhengyuan Zhou, Jose H. Blanchet:
Distributionally Robust Batch Contextual Bandits. Manag. Sci. 69(10): 5772-5793 (2023) - [j22]Xiaoqin Zhang, Jingjing Zheng, Di Wang, Guiying Tang, Zhengyuan Zhou, Zhouchen Lin:
Structured Sparsity Optimization With Non-Convex Surrogates of $\ell _{2,0}$ℓ2,0-Norm: A Unified Algorithmic Framework. IEEE Trans. Pattern Anal. Mach. Intell. 45(5): 6386-6402 (2023) - [c60]Shengbo Wang, Nian Si, José H. Blanchet, Zhengyuan Zhou:
A Finite Sample Complexity Bound for Distributionally Robust Q-learning. AISTATS 2023: 3370-3398 - [c59]Zijian Liu, Jiawei Zhang, Zhengyuan Zhou:
Breaking the Lower Bound with (Little) Structure: Acceleration in Non-Convex Stochastic Optimization with Heavy-Tailed Noise. COLT 2023: 2266-2290 - [i42]Zhipeng Liang, Xiaoteng Ma, Jose H. Blanchet, Jiheng Zhang, Zhengyuan Zhou:
Single-Trajectory Distributionally Robust Reinforcement Learning. CoRR abs/2301.11721 (2023) - [i41]Zijian Liu, Perry Dong, Srikanth Jagabathula, Zhengyuan Zhou:
Near-Optimal High-Probability Convergence for Non-Convex Stochastic Optimization with Variance Reduction. CoRR abs/2302.06032 (2023) - [i40]Zijian Liu, Jiawei Zhang, Zhengyuan Zhou:
Breaking the Lower Bound with (Little) Structure: Acceleration in Non-Convex Stochastic Optimization with Heavy-Tailed Noise. CoRR abs/2302.06763 (2023) - [i39]Shengbo Wang, Nian Si, Jose H. Blanchet, Zhengyuan Zhou:
A Finite Sample Complexity Bound for Distributionally Robust Q-learning. CoRR abs/2302.13203 (2023) - [i38]Zijian Liu, Zhengyuan Zhou:
Stochastic Nonsmooth Convex Optimization with Heavy-Tailed Noises. CoRR abs/2303.12277 (2023) - [i37]Shengbo Wang, Nian Si, Jose H. Blanchet, Zhengyuan Zhou:
Sample Complexity of Variance-reduced Distributionally Robust Q-learning. CoRR abs/2305.18420 (2023) - [i36]Michael I. Jordan, Tianyi Lin, Zhengyuan Zhou:
Adaptive, Doubly Optimal No-Regret Learning in Strongly Monotone and Exp-Concave Games with Gradient Feedback. CoRR abs/2310.14085 (2023) - [i35]Shengbo Wang, Nian Si, Jose H. Blanchet, Zhengyuan Zhou:
On the Foundation of Distributionally Robust Reinforcement Learning. CoRR abs/2311.09018 (2023) - [i34]Zijian Liu, Zhengyuan Zhou:
Revisiting the Last-Iterate Convergence of Stochastic Gradient Methods. CoRR abs/2312.08531 (2023) - 2022
- [j21]Zhimei Ren, Zhengyuan Zhou, Jayant R. Kalagnanam:
Batched Learning in Generalized Linear Contextual Bandits With General Decision Sets. IEEE Control. Syst. Lett. 6: 37-42 (2022) - [j20]Yuexiang Zhai, Christina Baek, Zhengyuan Zhou, Jiantao Jiao, Yi Ma:
Computational Benefits of Intermediate Rewards for Goal-Reaching Policy Learning. J. Artif. Intell. Res. 73: 847-896 (2022) - [j19]Ilai Bistritz, Zhengyuan Zhou, Xi Chen, Nicholas Bambos, José H. Blanchet:
No Weighted-Regret Learning in Adversarial Bandits with Delays. J. Mach. Learn. Res. 23: 139:1-139:43 (2022) - [j18]Shi Dong, Benjamin Van Roy, Zhengyuan Zhou:
Simple Agent, Complex Environment: Efficient Reinforcement Learning with Agent States. J. Mach. Learn. Res. 23: 255:1-255:54 (2022) - [j17]Zhengyuan Zhou, Panayotis Mertikopoulos, Nicholas Bambos, Peter W. Glynn, Yinyu Ye:
Distributed Stochastic Optimization with Large Delays. Math. Oper. Res. 47(3): 2082-2111 (2022) - [j16]Ilai Bistritz, Andrew Ward, Zhengyuan Zhou, Nicholas Bambos:
Smart Greedy Distributed Energy Allocation: A Random Games Approach. IEEE Trans. Autom. Control. 67(5): 2208-2220 (2022) - [c58]Nathan Kallus, Xiaojie Mao, Kaiwen Wang, Zhengyuan Zhou:
Doubly Robust Distributionally Robust Off-Policy Evaluation and Learning. ICML 2022: 10598-10632 - [c57]Zijian Liu, Qinxun Bai, Jose H. Blanchet, Perry Dong, Wei Xu, Zhengqing Zhou, Zhengyuan Zhou:
Distributionally Robust Q-Learning. ICML 2022: 13623-13643 - [c56]Yan Chen, Perry Dong, Qinxun Bai, Maria Dimakopoulou, Wei Xu, Zhengyuan Zhou:
Society of Agents: Regret Bounds of Concurrent Thompson Sampling. NeurIPS 2022 - [c55]Wei Zhang, Yanjun Han, Zhengyuan Zhou, Aaron Flores, Tsachy Weissman:
Leveraging the Hints: Adaptive Bidding in Repeated First-Price Auctions. NeurIPS 2022 - [i33]Nathan Kallus, Xiaojie Mao, Kaiwen Wang, Zhengyuan Zhou:
Doubly Robust Distributionally Robust Off-Policy Evaluation and Learning. CoRR abs/2202.09667 (2022) - [i32]Boxiao Chen, Jiashuo Jiang, Jiawei Zhang, Zhengyuan Zhou:
Learning to Order for Inventory Systems with Lost Sales and Uncertain Supplies. CoRR abs/2207.04550 (2022) - [i31]Zhaonan Qu, Wenzhi Gao, Oliver Hinder, Yinyu Ye, Zhengyuan Zhou:
Optimal Diagonal Preconditioning: Theory and Practice. CoRR abs/2209.00809 (2022) - [i30]Xiaoteng Ma, Zhipeng Liang, Jose H. Blanchet, Mingwen Liu, Li Xia, Jiheng Zhang, Qianchuan Zhao, Zhengyuan Zhou:
Distributionally Robust Offline Reinforcement Learning with Linear Function Approximation. CoRR abs/2209.06620 (2022) - [i29]Wei Zhang, Yanjun Han, Zhengyuan Zhou, Aaron Flores, Tsachy Weissman:
Leveraging the Hints: Adaptive Bidding in Repeated First-Price Auctions. CoRR abs/2211.06358 (2022) - 2021
- [j15]Zhengyuan Zhou, Panayotis Mertikopoulos, Aris L. Moustakas, Nicholas Bambos, Peter W. Glynn:
Robust Power Management via Learning and Game Design. Oper. Res. 69(1): 331-345 (2021) - [j14]Xiaoqin Zhang, Di Wang, Zhengyuan Zhou, Yi Ma:
Robust Low-Rank Tensor Recovery with Rectification and Alignment. IEEE Trans. Pattern Anal. Mach. Intell. 43(1): 238-255 (2021) - [c54]Zhengqing Zhou, Qinxun Bai, Zhengyuan Zhou, Linhai Qiu, Jose H. Blanchet, Peter W. Glynn:
Finite-Sample Regret Bound for Distributionally Robust Offline Tabular Reinforcement Learning. AISTATS 2021: 3331-3339 - [c53]Zhimei Ren, Zhengyuan Zhou, Jayant R. Kalagnanam:
Batched Learning in Generalized Linear Contextual Bandits with General Decision Sets. ACC 2021: 4958-4963 - [c52]Wei Zhang, Brendan Kitts, Yanjun Han, Zhengyuan Zhou, Tingyu Mao, Hao He, Shengjun Pan, Aaron Flores, San Gultekin, Tsachy Weissman:
MEOW: A Space-Efficient Nonparametric Bid Shading Algorithm. KDD 2021: 3928-3936 - [c51]Jingwei Zhang, Zhuoran Yang, Zhengyuan Zhou, Zhaoran Wang:
Provably Sample Efficient Reinforcement Learning in Competitive Linear Quadratic Systems. L4DC 2021: 597-598 - [c50]Maria Dimakopoulou, Zhimei Ren, Zhengyuan Zhou:
Online Multi-Armed Bandits with Adaptive Inference. NeurIPS 2021: 1939-1951 - [i28]Shi Dong, Benjamin Van Roy, Zhengyuan Zhou:
Simple Agent, Complex Environment: Efficient Reinforcement Learning with Agent State. CoRR abs/2102.05261 (2021) - [i27]Maria Dimakopoulou, Zhimei Ren, Zhengyuan Zhou:
Doubly-Adaptive Thompson Sampling for Multi-Armed and Contextual Bandits. CoRR abs/2102.13202 (2021) - [i26]Chaobing Song, Zhengyuan Zhou, Yichao Zhou, Yong Jiang, Yi Ma:
Optimistic Dual Extrapolation for Coherent Non-monotone Variational Inequalities. CoRR abs/2103.04410 (2021) - [i25]Ilai Bistritz, Zhengyuan Zhou, Xi Chen, Nicholas Bambos, Jose H. Blanchet:
No Discounted-Regret Learning in Adversarial Bandits with Delays. CoRR abs/2103.04550 (2021) - [i24]Ruohan Zhan, Zhimei Ren, Susan Athey, Zhengyuan Zhou:
Policy Learning with Adaptively Collected Data. CoRR abs/2105.02344 (2021) - [i23]Zhengyuan Zhou, Panayotis Mertikopoulos, Nicholas Bambos, Peter W. Glynn, Yinyu Ye:
Distributed stochastic optimization with large delays. CoRR abs/2107.02919 (2021) - [i22]Yuexiang Zhai, Christina Baek, Zhengyuan Zhou, Jiantao Jiao, Yi Ma:
Computational Benefits of Intermediate Rewards for Hierarchical Planning. CoRR abs/2107.03961 (2021) - [i21]Tianyi Lin, Zhengyuan Zhou, Wenjia Ba, Jiawei Zhang:
Optimal No-Regret Learning in Strongly Monotone Games with Bandit Feedback. CoRR abs/2112.02856 (2021) - 2020
- [j13]Erik Sverdrup, Ayush Kanodia, Zhengyuan Zhou, Susan Athey, Stefan Wager:
policytree: Policy learning via doubly robust empirical welfare maximization over trees. J. Open Source Softw. 5(55): 2232 (2020) - [j12]Zhengyuan Zhou, Jonathan Richard Shewchuk, Dusan M. Stipanovic, Haomiao Huang, Claire J. Tomlin:
Smarter Lions: Efficient Cooperative Pursuit in General Bounded Arenas. SIAM J. Control. Optim. 58(2): 1229-1256 (2020) - [j11]Zhengyuan Zhou, Panayotis Mertikopoulos, Nicholas Bambos, Stephen P. Boyd, Peter W. Glynn:
On the Convergence of Mirror Descent beyond Stochastic Convex Programming. SIAM J. Optim. 30(1): 687-716 (2020) - [c49]Zhaolin Ren, Zhengyuan Zhou, Linhai Qiu, Ajay Deshpande, Jayant Kalagnanam:
Delay-Adaptive Distributed Stochastic Optimization. AAAI 2020: 5503-5510 - [c48]Yuexiang Zhai, Hermish Mehta, Zhengyuan Zhou, Yi Ma:
Understanding l4-based Dictionary Learning: Interpretation, Stability, and Robustness. ICLR 2020 - [c47]Amélie Héliou, Panayotis Mertikopoulos, Zhengyuan Zhou:
Gradient-free Online Learning in Continuous Games with Delayed Rewards. ICML 2020: 4172-4181 - [c46]Tianyi Lin, Zhengyuan Zhou, Panayotis Mertikopoulos, Michael I. Jordan:
Finite-Time Last-Iterate Convergence for Multi-Agent Learning in Games. ICML 2020: 6161-6171 - [c45]Nian Si, Fan Zhang, Zhengyuan Zhou, Jose H. Blanchet:
Distributionally Robust Policy Evaluation and Learning in Offline Contextual Bandits. ICML 2020: 8884-8894 - [c44]Chaobing Song, Zhengyuan Zhou, Yichao Zhou, Yong Jiang, Yi Ma:
Optimistic Dual Extrapolation for Coherent Non-monotone Variational Inequalities. NeurIPS 2020 - [i20]Tianyi Lin, Zhengyuan Zhou, Panayotis Mertikopoulos, Michael I. Jordan:
Finite-Time Last-Iterate Convergence for Multi-Agent Learning in Games. CoRR abs/2002.09806 (2020) - [i19]Jose H. Blanchet, Renyuan Xu, Zhengyuan Zhou:
Delay-Adaptive Learning in Generalized Linear Contextual Bandits. CoRR abs/2003.05174 (2020) - [i18]Zhaonan Qu, Yinyu Ye, Zhengyuan Zhou:
Diagonal Preconditioning: Theory and Algorithms. CoRR abs/2003.07545 (2020) - [i17]Yanjun Han, Zhengyuan Zhou, Tsachy Weissman:
Optimal No-regret Learning in Repeated First-price Auctions. CoRR abs/2003.09795 (2020) - [i16]Yanjun Han, Zhengqing Zhou, Zhengyuan Zhou, Jose H. Blanchet, Peter W. Glynn, Yinyu Ye:
Sequential Batch Learning in Finite-Action Linear Contextual Bandits. CoRR abs/2004.06321 (2020) - [i15]Xiaoteng Ma, Qiyuan Zhang, Li Xia, Zhengyuan Zhou, Jun Yang, Qianchuan Zhao:
Distributional Soft Actor Critic for Risk Sensitive Learning. CoRR abs/2004.14547 (2020) - [i14]Nian Si, Fan Zhang, Zhengyuan Zhou, Jose H. Blanchet:
Distributional Robust Batch Contextual Bandits. CoRR abs/2006.05630 (2020) - [i13]Amélie Héliou, Panayotis Mertikopoulos, Zhengyuan Zhou:
Gradient-free Online Learning in Games with Delayed Rewards. CoRR abs/2006.10911 (2020) - [i12]Yanjun Han, Zhengyuan Zhou, Aaron Flores, Erik Ordentlich, Tsachy Weissman:
Learning to Bid Optimally and Efficiently in Adversarial First-price Auctions. CoRR abs/2007.04568 (2020) - [i11]Zhaonan Qu, Kaixiang Lin, Jayant Kalagnanam, Zhaojian Li, Jiayu Zhou, Zhengyuan Zhou:
Federated Learning's Blessing: FedAvg has Linear Speedup. CoRR abs/2007.05690 (2020) - [i10]Zhimei Ren, Zhengyuan Zhou:
Dynamic Batch Learning in High-Dimensional Sparse Linear Contextual Bandits. CoRR abs/2008.11918 (2020) - [i9]Zhaolin Ren, Aoxiao Zhong, Zhengyuan Zhou, Na Li:
Federated LQR: Learning through Sharing. CoRR abs/2011.01815 (2020)
2010 – 2019
- 2019
- [j10]Panayotis Mertikopoulos, Zhengyuan Zhou:
Learning in games with continuous action sets and unknown payoff functions. Math. Program. 173(1-2): 465-507 (2019) - [j9]Hao Cheng, Zhengyuan Zhou, Yanqing Li, Wenyi Huang, Jun Feng, Tingfan Tang, Lijun Li:
Electrochemiluminescence Sensor Based on Electrospun Three-Dimensional Carbon Nanofibers for the Detection of Difenidol Hydrochloride. Sensors 19(15): 3315 (2019) - [c43]Maria Dimakopoulou, Zhengyuan Zhou, Susan Athey, Guido Imbens:
Balanced Linear Contextual Bandits. AAAI 2019: 3445-3453 - [c42]Ilai Bistritz, Andrew Ward, Zhengyuan Zhou, Nicholas Bambos:
Smart Greedy Distributed Allocation in Microgrids. ICC 2019: 1-6 - [c41]Andrew Ward, Zhengyuan Zhou, Nicholas Bambos, Ellen Wang, David Scheinker:
Anesthesiologist Surgery Assignments using Policy Learning. ICC 2019: 1-6 - [c40]Andrew Ward, Zhengyuan Zhou, Nicholas Bambos:
Bidding-Based Dynamic Power Pricing Scheme in Smart Grids. ICNC 2019: 729-734 - [c39]Zhengyuan Zhou, Renyuan Xu, Jose H. Blanchet:
Learning in Generalized Linear Contextual Bandits with Stochastic Delays. NeurIPS 2019: 5198-5209 - [c38]Ilai Bistritz, Zhengyuan Zhou, Xi Chen, Nicholas Bambos, Jose H. Blanchet:
Online EXP3 Learning in Adversarial Bandits with Delayed Feedback. NeurIPS 2019: 11345-11354 - [i8]Shi Dong, Benjamin Van Roy, Zhengyuan Zhou:
Provably Efficient Reinforcement Learning with Aggregated States. CoRR abs/1912.06366 (2019) - 2018
- [j8]Zhengyuan Zhou, Jerry Ding, Haomiao Huang, Ryo Takei, Claire J. Tomlin:
Efficient path planning algorithms in reach-avoid problems. Autom. 89: 28-36 (2018) - [j7]Zhengyuan Zhou, Nicholas Bambos, Peter W. Glynn:
Deterministic and Stochastic Wireless Network Games: Equilibrium, Dynamics, and Price of Anarchy. Oper. Res. 66(6): 1498-1516 (2018) - [j6]Zhengyuan Zhou, Michael Bloem, Nicholas Bambos:
Infinite Time Horizon Maximum Causal Entropy Inverse Reinforcement Learning. IEEE Trans. Autom. Control. 63(9): 2787-2802 (2018) - [c37]Saied Mehdian, Zhengyuan Zhou, Nicholas Bambos:
Robustness of Join-the-Shortest-Queue Scheduling to Communication Delay. ACC 2018: 3708-3713 - [c36]Daniel Miller, Zhengyuan Zhou, Nicholas Bambos, Irad Ben-Gal:
Sensing-Constrained Power Control in Digital Health. ACC 2018: 4213-4220 - [c35]Andrew Ward, Zhengyuan Zhou, Panayotis Mertikopoulos, Nicholas Bambos:
Power Control with Random Delays: Robust Feedback Averaging. CDC 2018: 7040-7045 - [c34]Daniel Miller, Zhengyuan Zhou, Nicholas Bambos, Irad Ben-Gal:
Optimal Sensing for Patient Health Monitoring. ICC 2018: 1-7 - [c33]Lu Jiang, Zhengyuan Zhou, Thomas Leung, Li-Jia Li, Li Fei-Fei:
MentorNet: Learning Data-Driven Curriculum for Very Deep Neural Networks on Corrupted Labels. ICML 2018: 2309-2318 - [c32]Zhengyuan Zhou, Panayotis Mertikopoulos, Nicholas Bambos, Peter W. Glynn, Yinyu Ye, Li-Jia Li, Li Fei-Fei:
Distributed Asynchronous Optimization with Unbounded Delays: How Slow Can You Go? ICML 2018: 5965-5974 - [c31]Zhengyuan Zhou, Yong Zhou, Dengqing Tang, Kuang Zhao, Tianjiang Hu:
Micro-UAV onboard vehicle detection: architecture and experiments. ISR 2018: 539-544 - [c30]Zhengyuan Zhou, Panayotis Mertikopoulos, Susan Athey, Nicholas Bambos, Peter W. Glynn, Yinyu Ye:
Learning in Games with Lossy Feedback. NeurIPS 2018: 5140-5150 - [i7]Zhengyuan Zhou, Susan Athey, Stefan Wager:
Offline Multi-Action Policy Learning: Generalization and Optimization. CoRR abs/1810.04778 (2018) - [i6]Maria Dimakopoulou, Zhengyuan Zhou, Susan Athey, Guido Imbens:
Balanced Linear Contextual Bandits. CoRR abs/1812.06227 (2018) - 2017
- [j5]Neal Master, Zhengyuan Zhou, Daniel Miller, David Scheinker, Nicholas Bambos, Peter W. Glynn:
Improving predictions of pediatric surgical durations with supervised learning. Int. J. Data Sci. Anal. 4(1): 35-52 (2017) - [j4]Mo Chen, Zhengyuan Zhou, Claire J. Tomlin:
Multiplayer Reach-Avoid Games via Pairwise Outcomes. IEEE Trans. Autom. Control. 62(3): 1451-1457 (2017) - [j3]Li Xia, Daniel Miller, Zhengyuan Zhou, Nicholas Bambos:
Service Rate Control of Tandem Queues With Power Constraints. IEEE Trans. Autom. Control. 62(10): 5111-5123 (2017) - [c29]Saied Mehdian, Zhengyuan Zhou, Nicholas Bambos:
Join-the-shortest-queue scheduling with delay. ACC 2017: 1747-1752 - [c28]Neal Master, Zhengyuan Zhou, Nicholas Bambos:
An infinite dimensional model for a single server priority queue. ACC 2017: 1753-1758 - [c27]Kevin Schubert, Neal Master, Zhengyuan Zhou, Nicholas Bambos:
Asynchronous best-response dynamics for resource allocation games in cloud computing. ACC 2017: 4613-4618 - [c26]Zhengyuan Zhou, Panayotis Mertikopoulos, Aris L. Moustakas, Nicholas Bambos, Peter W. Glynn:
Mirror descent learning in continuous games. CDC 2017: 5776-5783 - [c25]Neal Master, Zhengyuan Zhou, Nicholas Bambos:
An infinite dimensional model for a many server priority queue. CISS 2017: 1-6 - [c24]Zhengyuan Zhou, Panayotis Mertikopoulos, Aris L. Moustakas, Saied Mehdian, Nicholas Bambos, Peter W. Glynn:
Stable Power Control in Wireless Networks via Dual Averaging. GLOBECOM 2017: 1-6 - [c23]Daniel Miller, Li Xia, Zhengyuan Zhou, Nicholas Bambos:
Dynamic control of data center network and computation resources. ICNC 2017: 374-380 - [c22]Zhengyuan Zhou, Panayotis Mertikopoulos, Nicholas Bambos, Peter W. Glynn, Claire J. Tomlin:
Countering Feedback Delays in Multi-Agent Learning. NIPS 2017: 6171-6181 - [c21]Zhengyuan Zhou, Panayotis Mertikopoulos, Nicholas Bambos, Stephen P. Boyd, Peter W. Glynn:
Stochastic Mirror Descent in Variationally Coherent Optimization Problems. NIPS 2017: 7040-7049 - [c20]Saied Mehdian, Zhengyuan Zhou, Nicholas Bambos:
Longest-queue-first scheduling with intermittent sampling. PIMRC 2017: 1-5 - [c19]Aris L. Moustakas, Panayotis Mertikopoulos, Zhengyuan Zhou, Nick Bambos:
Least action routing: Identifying the optimal path in a wireless relay network. PIMRC 2017: 1-5 - [i5]Neal Master, Zhengyuan Zhou, Nicholas Bambos:
An Infinite Dimensional Model for a Many Server Priority Queue. CoRR abs/1701.01328 (2017) - [i4]Zhengyuan Zhou, Panayotis Mertikopoulos, Nicholas Bambos, Stephen P. Boyd, Peter W. Glynn:
Mirror descent in non-convex stochastic programming. CoRR abs/1706.05681 (2017) - [i3]Lu Jiang, Zhengyuan Zhou, Thomas Leung, Li-Jia Li, Li Fei-Fei:
MentorNet: Regularizing Very Deep Neural Networks on Corrupted Labels. CoRR abs/1712.05055 (2017) - 2016
- [j2]Zhengyuan Zhou, Wei Zhang, Jerry Ding, Haomiao Huang, Dusan M. Stipanovic, Claire J. Tomlin:
Cooperative pursuit with Voronoi partitions. Autom. 72: 64-72 (2016) - [j1]Siddhartha Banerjee, Ramesh Johari, Zhengyuan Zhou:
The Importance of Exploration in Online Marketplaces. IEEE Internet Comput. 20(1): 20-26 (2016) - [c18]Zhengyuan Zhou, Benjamin Yolken, Reiko Ann Miura-Ko, Nicholas Bambos:
A game-theoretical formulation of influence networks. ACC 2016: 3802-3807 - [c17]Zhengyuan Zhou, Peter W. Glynn, Nicholas Bambos:
Repeated games for power control in wireless communications: Equilibrium and regret. CDC 2016: 3603-3610 - [c16]Zhengyuan Zhou, Daniel Miller, Neal Master, David Scheinker, Nicholas Bambos, Peter W. Glynn:
Detecting Inaccurate Predictions of Pediatric Surgical Durations. DSAA 2016: 452-457 - [c15]Zhengyuan Zhou, Nicholas Bambos, Peter W. Glynn:
Dynamics on Linear Influence Network Games Under Stochastic Environments. GameSec 2016: 114-126 - [c14]Zhengyuan Zhou, Daniel Miller, Nicholas Bambos, Peter W. Glynn:
A Stochastic Stability Characterization of the Foschini-Miljanic Algorithm in Random Wireless Networks. GLOBECOM 2016: 1-6 - [i2]Neal Master, Zhengyuan Zhou, Nicholas Bambos:
An Infinite Dimensional Model for A Single Server Priority Queue. CoRR abs/1609.07996 (2016) - 2015
- [c13]Zhengyuan Zhou, Nicholas Bambos:
A general model for resource allocation in utility computing. ACC 2015: 1746-1751 - [c12]Zhengyuan Zhou, Nicholas Bambos:
Wireless communications games in fixed and random environments. CDC 2015: 1637-1642 - [c11]Zhengyuan Zhou, Nicholas Bambos:
Target-rate driven resource sharing in queueing systems. CDC 2015: 4940-4945 - [c10]Daniel Miller, Neal Master, Zhengyuan Zhou, Nicholas Bambos:
Scalable Data Center Power Management via a Global Stress Signal. GLOBECOM 2015: 1-7 - 2014
- [c9]Xiaoqin Zhang, Zhengyuan Zhou, Di Wang, Yi Ma:
Hybrid Singular Value Thresholding for Tensor Completion. AAAI 2014: 1362-1368 - [c8]Mo Chen, Zhengyuan Zhou, Claire J. Tomlin:
Multiplayer reach-avoid games via low dimensional solutions and maximum matching. ACC 2014: 1444-1449 - [c7]Zhengyuan Zhou, Michael P. Vitus, Claire J. Tomlin:
Convexity verification for a hybrid chance constrained method in stochastic control problems. ACC 2014: 4494-4499 - [c6]Mo Chen, Zhengyuan Zhou, Claire J. Tomlin:
A path defense approach to the multiplayer reach-avoid game. CDC 2014: 2420-2426 - [c5]Siddhartha Banerjee, Zhengyuan Zhou, Ramesh Johari:
The importance of exploration in online marketplaces. CDC 2014: 3499-3504 - [c4]Shih-Yuan Liu, Zhengyuan Zhou, Claire J. Tomlin, J. Karl Hedrick:
Evasion of a team of dubins vehicles from a hidden pursuer. ICRA 2014: 6771-6776 - [i1]Dawsen Hwang, Patrick Jaillet, Zhengyuan Zhou:
Distributed Multi-Depot Routing without Communications. CoRR abs/1412.2123 (2014) - 2013
- [c3]Shih-Yuan Liu, Zhengyuan Zhou, Claire J. Tomlin, J. Karl Hedrick:
Evasion as a team against a faster pursuer. ACC 2013: 5368-5373 - [c2]Xiaoqin Zhang, Di Wang, Zhengyuan Zhou, Yi Ma:
Simultaneous Rectification and Alignment via Robust Recovery of Low-rank Tensors. NIPS 2013: 1637-1645 - 2012
- [c1]Zhengyuan Zhou, Ryo Takei, Haomiao Huang, Claire J. Tomlin:
A general, open-loop formulation for reach-avoid games. CDC 2012: 6501-6506
Coauthor Index
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