Sihan Zeng

Publication Activity (10 Years)

Years Active: 2017-2024
Publications (10 Years): 33

Top Topics

Compressive Sensing

Stochastic Approximation

Reinforcement Learning

Top Venues

Publications

Sihan Zeng, Thinh T. Doan, Justin Romberg
A Two-Time-Scale Stochastic Optimization Framework with Applications in Control and Reinforcement Learning. SIAM J. Optim. 34 (1) (2024)
Sihan Zeng, Thinh T. Doan
Fast two-time-scale stochastic gradient method with applications in reinforcement learning. COLT (2024)
Sihan Zeng, Thinh T. Doan
Fast Two-Time-Scale Stochastic Gradient Method with Applications in Reinforcement Learning. CoRR (2024)
Sihan Zeng, Thinh T. Doan, Justin Romberg
Natural Policy Gradient and Actor Critic Methods for Constrained Multi-Task Reinforcement Learning. CoRR (2024)
Sihan Zeng, Youngdae Kim, Yuxuan Ren, Kibaek Kim
QCQP-Net: Reliably Learning Feasible Alternating Current Optimal Power Flow Solutions Under Constraints. CoRR (2024)
Sihan Zeng, Youngdae Kim, Yuxuan Ren, Kibaek Kim
QCQP-Net: Reliably learning feasible alternating current optimal power flow solutions under constraints. L4DC (2024)
Parisa Hassanzadeh, Eleonora Kreacic, Sihan Zeng, Yuchen Xiao, Sumitra Ganesh
Sequential Fair Resource Allocation under a Markov Decision Process Framework. CoRR (2023)
Keyi Yu, Yu Wang, Sihan Zeng, Chen Liang, Xiaoyu Bai, Dachi Chen, Wenping Wang
InkGAN: Generative Adversarial Networks for Ink-And-Wash Style Transfer of Photographs. Adv. Artif. Intell. Mach. Learn. 3 (2) (2023)
Sihan Zeng, Sujay Bhatt, Eleonora Kreacic, Parisa Hassanzadeh, Alec Koppel, Sumitra Ganesh
Near-Optimal Fair Resource Allocation for Strategic Agents without Money: A Data-Driven Approach. CoRR (2023)
Sihan Zeng, Thinh T. Doan, Justin Romberg
Connected Superlevel Set in (Deep) Reinforcement Learning and its Application to Minimax Theorems. NeurIPS (2023)
Sihan Zeng, Thinh T. Doan, Justin Romberg
Connected Superlevel Set in (Deep) Reinforcement Learning and its Application to Minimax Theorems. CoRR (2023)
Sihan Zeng, Thinh T. Doan, Justin Romberg
Finite-Time Convergence Rates of Decentralized Stochastic Approximation With Applications in Multi-Agent and Multi-Task Learning. IEEE Trans. Autom. Control. 68 (5) (2023)
Parisa Hassanzadeh, Eleonora Kreacic, Sihan Zeng, Yuchen Xiao, Sumitra Ganesh
Sequential Fair Resource Allocation under a Markov Decision Process Framework. ICAIF (2023)
Sihan Zeng, Thinh T. Doan, Justin Romberg
Finite-Time Complexity of Online Primal-Dual Natural Actor-Critic Algorithm for Constrained Markov Decision Processes. CDC (2022)
Sihan Zeng, Thinh T. Doan, Justin Romberg
Regularized Gradient Descent Ascent for Two-Player Zero-Sum Markov Games. NeurIPS (2022)
Sihan Zeng, Zhongliang Pan
An unsupervised font style transfer model based on generative adversarial networks. Multim. Tools Appl. 81 (4) (2022)
Sihan Zeng, Thinh T. Doan, Justin Romberg
Regularized Gradient Descent Ascent for Two-Player Zero-Sum Markov Games. CoRR (2022)
Sihan Zeng, Malik Aqeel Anwar, Thinh T. Doan, Arijit Raychowdhury, Justin Romberg
A decentralized policy gradient approach to multi-task reinforcement learning. UAI (2021)
Sihan Zeng, Thinh T. Doan, Justin Romberg
A Two-Time-Scale Stochastic Optimization Framework with Applications in Control and Reinforcement Learning. CoRR (2021)
Sihan Zeng, Alyssa Kody, Youngdae Kim, Kibaek Kim, Daniel K. Molzahn
A Reinforcement Learning Approach to Parameter Selection for Distributed Optimization in Power Systems. CoRR (2021)
Huandong Wang, Sihan Zeng, Yong Li, Depeng Jin
Predictability and Prediction of Human Mobility Based on Application-Collected Location Data. IEEE Trans. Mob. Comput. 20 (7) (2021)
Sihan Zeng, Thinh T. Doan, Justin Romberg
Finite-Time Complexity of Online Primal-Dual Natural Actor-Critic Algorithm for Constrained Markov Decision Processes. CoRR (2021)
Sihan Zeng, Thinh T. Doan, Justin Romberg
Finite-Time Analysis of Decentralized Stochastic Approximation with Applications in Multi-Agent and Multi-Task Learning. CDC (2021)
Huandong Wang, Sihan Zeng, Yong Li, Pengyu Zhang, Depeng Jin
Human Mobility Prediction Using Sparse Trajectory Data. IEEE Trans. Veh. Technol. 69 (9) (2020)
Sihan Zeng, Aqeel Anwar, Thinh T. Doan, Justin Romberg, Arijit Raychowdhury
A Decentralized Policy Gradient Approach to Multi-task Reinforcement Learning. CoRR (2020)
Sihan Zeng, Thinh T. Doan, Justin Romberg
Finite-Time Analysis of Decentralized Stochastic Approximation with Applications in Multi-Agent and Multi-Task Learning. CoRR (2020)
Xinlei Chen, Carlos Ruiz Dominguez, Sihan Zeng, Liyao Gao, Aveek Purohit, Stefano Carpin, Pei Zhang
H-DrunkWalk: Collaborative and Adaptive Navigation for Heterogeneous MAV Swarm. ACM Trans. Sens. Networks 16 (2) (2020)
Huandong Wang, Yong Li, Sihan Zeng, Gang Wang, Pengyu Zhang, Pan Hui, Depeng Jin
Modeling Spatio-Temporal App Usage for a Large User Population. Proc. ACM Interact. Mob. Wearable Ubiquitous Technol. 3 (1) (2019)
Sihan Zeng, Jose Manuel Monsalve Diaz, Siddhisanket Raskar
Toward A High-Performance Emulation Platformfor Brain-Inspired Intelligent SystemsExploring Dataflow-Based Execution Model and Beyond. COMPSAC (2) (2019)
Shaojie Xu, Sihan Zeng, Justin Romberg
Fast Compressive Sensing Recovery Using Generative Models with Structured Latent Variables. CoRR (2019)
Xuesi Zhou, Haoqi Xiong, Sihan Zeng, Xiangling Fu, Ji Wu
An approach for medical event detection in Chinese clinical notes of electronic health records. BMC Medical Informatics Decis. Mak. (2) (2019)
Shaojie Xu, Sihan Zeng, Justin Romberg
Fast Compressive Sensing Recovery Using Generative Models with Structured Latent Variables. ICASSP (2019)
Sihan Zeng, Huandong Wang, Yong Li, Depeng Jin
Predictability and Prediction of Human Mobility Based on Application-Collected Location Data. MASS (2017)